system

Abstract

Provide a system. An input means for inputting contract information; a transmission means for transmitting the input contract information to a server; a draft generation means for generating a contract draft based on contract information input in the server; a transmission means for transmitting the generated contract draft to a terminal; A means for a user to amend the contract draft; a sending means for sending the amended draft contract to the server; a final contract generation means for generating a final contract that reflects the amendments; a means for providing the generated final contract; A system including:

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] The traditional process of creating contracts and approval documents is prone to manual input errors and time-consuming processes. It is also difficult to strictly apply templates, making it difficult to ensure a unified format. These issues result in inconsistent quality of contracts and approval documents and reduced work efficiency. [Means for solving the problem]

[0005] The present invention provides a system in which a user inputs contract information and approval request information, and a server automatically generates a draft of the contract and approval request based on the information. Specifically, the system includes the following means.

[0006] an input means for inputting contract information;

[0007] a transmission means for transmitting the input contract information to a server;

[0008] a draft generation means for generating a contract draft based on contract information input in the server;

[0009] a transmission means for transmitting the generated contract draft to a terminal;

[0010] A means for a user to amend the contract draft;

[0011] a sending means for sending the amended draft contract to the server;

[0012] a final contract generation means for generating a final contract that reflects the amendments;

[0013] a means for providing the generated final contract;

[0014] The generated contract drafts and approval drafts are generated using machine learning models, enabling accurate and efficient document creation.

[0015] "Input means" refers to a device or interface that allows a user to input contract information or approval information.

[0016] "Transmission means" refers to the communication means or protocol for transmitting input data to the server.

[0017] "Draft generation means" refers to software or algorithms that automatically generate drafts of contracts or approval documents based on information entered into the server.

[0018] "Modification means" refers to an interface or tool that allows a user to modify a generated draft.

[0019] "Final Agreement Generation Means" refers to software or algorithms that generate a final version of the agreement based on the revised draft.

[0020] "Means of provision" refers to the means for providing the generated final contract or request document to the user.

[0021] "Server" refers to a computer system that generates drafts of contracts and approval documents, stores data, and processes the data.

[0022] "Terminal" refers to a computer or mobile device used by a user to input, modify, and confirm contract information and approval information.

[0023] A "machine learning model" refers to an algorithm or program that learns from data and automates the generation of contracts and approval documents.

[0024] "Contract information" refers to information necessary for creating a contract (for example, the contracting party, contract contents, deadline, etc.).

[0025] "Approval information" refers to information necessary for creating a request (e.g., contract purpose, budget, risk assessment, etc.).

[0026] "Draft Agreement" refers to the first version of the Agreement generated by the Server.

[0027] "Draft Request" refers to the first version of the request generated by the server.

[0028] "Final Agreement" means the final version of the Agreement that reflects User's modifications.

[0029] "Final approval document" refers to the final version of the approval document that reflects the user's modifications. [Brief explanation of the drawings]

[0030] [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

[0031] 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.

[0032] First, the terms used in the following description will be explained.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] [First embodiment]

[0039] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0040] 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.

[0041] 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).

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0047] 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.

[0048] 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.

[0049] 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.

[0050] 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."

[0051] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments for implementing the program of this system will be described below.

[0052] System Overview

[0053] In this system, users use a terminal to input contract information and approval information, and then send that information to a server, which then automatically generates a draft of the contract or approval document and provides the final document.

[0054] Contract Creation

[0055] 1. The user enters the contract information using the terminal.

[0056] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount," and then indicates completion of input.

[0057] 2. The device sends the data to the server

[0058] The terminal sends the entered contract information to the server in a data format (e.g., JSON).

[0059] 3. The server generates a draft contract

[0060] The server analyzes the received contract information, selects an appropriate contract template using an AI model (e.g., an NLP-based template modeler), and automatically generates a contract draft. The generated draft is then converted back into a data format and sent to the terminal.

[0061] 4. User checks and edits the draft

[0062] The user can check the draft contract on the terminal and make any necessary changes, such as modifying the "contracting party information" or adding "payment terms."

[0063] 5. The device sends the correction data to the server

[0064] The terminal transmits the user's modifications to the server again.

[0065] 6. The server generates the final contract

[0066] The server generates a final version of the contract that reflects the amendments and provides it as a document such as a PDF file, which the user can download.

[0067] Drafting approval documents

[0068] 1. The user enters the approval information based on the contract information

[0069] The user reviews the final contract on the terminal and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval.

[0070] 2. The device sends the data to the server

[0071] The terminal transmits the input approval information to the server in data format.

[0072] 3. The server generates a draft request.

[0073] The server analyzes the received approval information, selects an appropriate approval template based on the AI ​​model, and automatically generates a draft approval document, which is then sent to the device.

[0074] 4. User checks and edits the draft

[0075] The user can review the draft approval document on their device and make any necessary corrections, such as changing the "budget details" or adding comments for the "risk assessment."

[0076] 5. The device sends the correction data to the server

[0077] The terminal transmits the user's modifications to the server again.

[0078] 6. The server generates the final approval document

[0079] The server generates a final version of the approval document that reflects the revisions and provides it as a document such as a PDF file, which the user can download.

[0080] Specific examples

[0081] Specific examples of contract creation

[0082] 1. The user enters the following: "Contract partner: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[0083] 2. The device sends this contract information to the server.

[0084] 3. The server generates a draft contract with the following information: "Contracting party: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[0085] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[0086] 5. The device sends the modifications to the server.

[0087] 6. The server finally generates the final contract with the following content: "Contract details: Sales of Product Y, Contract amount: 5 million yen, Contract expiration date: January 31, 2026" and provides it as a PDF file.

[0088] Specific examples of drafting approval documents

[0089] 1. The user enters approval information such as "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[0090] 2. The device sends this data to the server.

[0091] 3. The server generates a draft approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[0092] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[0093] 5. The device sends the modifications to the server.

[0094] 6. The server finally generates the final approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[0095] The above is a specific example of the operation of the embodiment of the present invention. This system improves the efficiency of the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[0096] The processing flow will be explained below.

[0097] Contract Creation Process

[0098] Step 1:

[0099] The user opens the contract creation page on their device and accesses the new contract creation form. The user enters the necessary information, such as the "contract date and time," "contract partner," "contract content," and "amount."

[0100] Step 2:

[0101] The terminal converts the entered contract information into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[0102] Step 3:

[0103] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information.

[0104] Step 4:

[0105] The server uses the AI ​​model to insert the contract information into the selected template and generate a draft contract, which is then converted back into a data format and sent to the device.

[0106] Step 5:

[0107] The user checks the draft contract displayed on the terminal and makes any necessary corrections, such as amending the contract amount or adding payment terms.

[0108] Step 6:

[0109] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[0110] Step 7:

[0111] The server generates the final contract based on the revised data, and saves the final contract as a PDF file or other document format.

[0112] Step 8:

[0113] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[0114] Approval document drafting process

[0115] Step 1:

[0116] The user checks the contract on their device and then moves to the page for creating a request for approval. The user enters information for the request, such as the purpose of the contract, the contracting party, the budget, and risk assessment, into the request for approval creation form.

[0117] Step 2:

[0118] The terminal converts the input approval information into a comprehensive data format (e.g., JSON) and sends it to the server, using the HTTPS protocol to ensure data security.

[0119] Step 3:

[0120] The server stores the received approval information in a database and uses it as input for the AI ​​model, which selects the most appropriate approval document template based on the approval information.

[0121] Step 4:

[0122] The server uses the AI ​​model to insert the approval request information into the selected template and generate a draft of the approval request document, which is then converted back into a data format and sent to the device.

[0123] Step 5:

[0124] The user checks the draft approval document displayed on the terminal and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments."

[0125] Step 6:

[0126] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[0127] Step 7:

[0128] The server generates a final approval document that reflects the corrections based on the corrected data, and saves the final approval document as a PDF file or other document format.

[0129] Step 8:

[0130] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[0131] Example 1

[0132] 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."

[0133] The traditional process for creating contracts and approval documents involves a lot of manual data entry, document generation, and editing, which results in low work efficiency and a high likelihood of problems due to input errors and inconsistent formats.In addition, it is difficult to standardize various documents, which can easily lead to variations in quality.

[0134] 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.

[0135] In this invention, the server includes input means for inputting contract data, transmission means for transmitting the input contract data to an information processing device, draft generation means for generating a contract draft based on the input contract data in the information processing device, transmission means for transmitting the generated contract draft to a terminal, correction means for the user to correct the contract draft, transmission means for transmitting the corrected contract draft to the information processing device, final contract generation means for generating a final contract reflecting the corrections, provision means for providing the generated final contract document, and means for using a generative AI model. This automates the process of creating contracts and approval documents, reducing input errors, improving work efficiency, and enabling the application of standardized formats.

[0136] "Input means" refers to a device or function that provides an interface for users to manually input contract data and approval data.

[0137] The "transmission means" is a communication device or function for transmitting data obtained by the input means to an information processing device or a server.

[0138] The "draft generation means" is a processing function or program for automatically generating a draft of a contract document or approval document based on the received data.

[0139] The "modification means" is a device or function that provides an interface for a user to check the generated draft of the contract document or approval document and modify the content as necessary.

[0140] The "final contract document generation means" is a processing function or program for generating a final contract document or approval document that reflects the corrections incorporated by the correction means.

[0141] The "means for providing" is a device or function for providing the generated final contract document or final approval document in a form that can be used by the user.

[0142] A "generative AI model" is an algorithm or system that uses machine learning techniques to select appropriate templates based on received data and automatically generate documents.

[0143] An "information processing device" is a computer or server that processes input data and provides various functions such as document generation.

[0144] A "terminal" is a device such as a personal computer, tablet, or smartphone that a user uses to enter contract information and approval information and to review and modify generated documents.

[0145] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments of this system will be described below.

[0146] Hardware and software used

[0147] Hardware: User devices (personal computers, tablets, smartphones, etc.), servers (high-performance computers)

[0148] Software: Web forms (front-end), server-side generative AI models (e.g., NLP-based template modelers)

[0149] System Overview

[0150] In this system, users input contract data and approval data using a terminal and send the information to a server, which then automatically generates draft contract and approval documents and provides the final documents. This streamlines the document creation process, reduces input errors, and enables the application of standardized formats.

[0151] Contract Creation Process

[0152] 1. The user enters the contract data using the terminal.

[0153] The user accesses the contract creation form using a web browser or a dedicated application, enters information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and clicks the "send" button.

[0154] 2. The device sends the data to the server

[0155] The terminal compiles the contract information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[0156] 3. The server generates a draft contract

[0157] The server parses the received JSON data and extracts the contract information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[0158] 4. User checks and edits the draft

[0159] The user can check the draft contract displayed on the terminal and modify it as necessary. For example, they can add information about the contracting party or modify the contract expiration date.

[0160] 5. The device sends the correction data to the server

[0161] The terminal sends the revised contract information again to the server in JSON format.

[0162] 6. The server generates the final contract

[0163] The server generates a final version of the contract that reflects the amendments, generates the final contract as a PDF document, and provides a link for the user to download it.

[0164] Approval document drafting process

[0165] 1. The user enters the approval request data based on the contract information

[0166] The user accesses the approval request creation form using a web browser or a dedicated application, reviews the final contract, and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment based on the contract's contents.

[0167] 2. The device sends the data to the server

[0168] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[0169] 3. The server generates a draft request.

[0170] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[0171] 4. User checks and edits the draft

[0172] The user can review the draft of the approval document displayed on the terminal and make corrections as necessary, for example, by changing the "budget details" or adding comments for the "risk assessment."

[0173] 5. The device sends the correction data to the server

[0174] The terminal sends the corrected approval information back to the server in JSON format.

[0175] 6. The server generates the final approval document

[0176] The server generates a final version of the approval document that reflects the changes, generates the final approval document as a PDF document, and provides a link for the user to download it.

[0177] Specific examples

[0178] Specific examples of contract creation

[0179] 1. The user enters the following information: "Contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[0180] 2. The device sends this contract information to the server.

[0181] 3. The server generates a draft contract with the following specifications: "Contracting party: a certain company, Contract content: product sales, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[0182] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[0183] 5. The device sends the modifications to the server.

[0184] 6. The server finally generates the final contract with the following content: "Contract details: product sales, contract amount: 5 million yen, contract expiration date: January 31, 2026" and provides it as a PDF file.

[0185] Specific examples of drafting approval documents

[0186] 1. The user enters the approval information, such as "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[0187] 2. The device sends this data to the server.

[0188] 3. The server generates a draft request form with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[0189] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[0190] 5. The device sends the modifications to the server.

[0191] 6. The server finally generates a final approval document with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[0192] As a result, the present invention streamlines the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[0193] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0194] Contract Creation Process

[0195] Step 1:

[0196] The user enters the contract data using the terminal.

[0197] The user accesses the contract creation form using a web browser or a dedicated application. They enter information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and then click the "Submit" button. The input data might include, for example, "contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[0198] Step 2:

[0199] The device sends data to the server

[0200] The terminal compiles the contract data entered by the user as JSON format data. The generated JSON data is sent to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format contract data, which is sent to the server.

[0201] Step 3:

[0202] The server generates a draft contract

[0203] The server parses the received JSON data and extracts the contract data. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract data to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated contract draft.

[0204] Step 4:

[0205] User reviews and edits the draft

[0206] The user checks the contract draft displayed on the terminal. If necessary, they modify the content, for example, adding "information about the contracting party" or modifying the "contract expiration date." The input data includes the content of the draft, especially the modified information. As a specific example of user behavior, the "contract expiration date" is modified to "January 31, 2026."

[0207] Step 5:

[0208] The device sends the correction data to the server

[0209] The terminal sends the modified contract data to the server again in JSON format. The input data contains the modified draft information, which is converted back to JSON format and provides the modified data that is sent to the server as output.

[0210] Step 6:

[0211] The server generates the final contract

[0212] The server generates a final contract that reflects the amendments. It generates the final contract as a PDF document and provides a link for the user to download it. The input data is the amended contract information, and the output is a PDF file of the final contract.

[0213] Approval document drafting process

[0214] Step 1:

[0215] The user enters approval data based on the contract information

[0216] The user accesses the approval request creation form using a web browser or a dedicated application. After reviewing the final contract, the user inputs information such as "contract purpose," "contract partner," "budget," and "risk assessment" based on the contract's contents. For example, input data might include "purpose: product sales, contract partner: certain company, budget: 5 million yen, risk: low."

[0217] Step 2:

[0218] The device sends data to the server

[0219] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format approval request data, which is sent to the server.

[0220] Step 3:

[0221] The server generates a draft request.

[0222] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated approval request draft.

[0223] Step 4:

[0224] User reviews and edits the draft

[0225] The user checks the draft approval document displayed on the terminal. If necessary, the user modifies the contents, for example, changing the "budget details" or adding a comment to the "risk assessment." The input data includes the contents of the draft, especially the modified information. As a specific example of user behavior, the user modifies the "budget" to "6 million yen."

[0226] Step 5:

[0227] The device sends the correction data to the server

[0228] The terminal sends the revised draft information to the server again in JSON format. The input data contains the revised draft information. It is converted back to JSON format and provides the revised data to be sent to the server as output.

[0229] Step 6:

[0230] The server generates the final approval document

[0231] The server generates a final approval document that reflects the revisions. The final approval document is generated as a PDF document and a link is provided for users to download. The input data is the revised approval document information, and the output is a PDF file of the final approval document.

[0232] (Application example 1)

[0233] 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."

[0234] The process of creating contracts and approval documents has traditionally been done manually, resulting in time-consuming and labor-intensive processes, and the possibility of input errors and format inconsistencies. Furthermore, in situations where speedy transactions are required, such as electronic payment services, there is a growing demand for an automated system for generating contracts and approval documents that can respond smoothly and instantly. This project aims to solve these problems.

[0235] 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.

[0236] In this invention, the server includes an input means for inputting contract information, a transmission means for transmitting the input contract information to the server, a draft generation means for generating a contract draft based on the input contract information in the server, a transmission means for transmitting the generated contract draft to a terminal, a correction means for a user to correct the contract draft, a transmission means for transmitting the corrected contract draft to the server, a final contract generation means for generating a final contract reflecting the corrections, a provision means for providing the generated final contract, an automation means for inputting contract information and approval request information using a smartphone and automatically generating a contract and approval request using an AI model, and a download means for making the generated final contract and approval request request downloadable in PDF format. This significantly streamlines the process of creating contracts and approval requests, reduces input errors, enables the application of standardized formats, and enables rapid use of electronic payment services.

[0237] "Contract information" refers to information necessary to create a contract, and specifically includes information such as the contracting party, contract contents, contract amount, contract period, etc.

[0238] The "transmission means" is a means for sending information entered by the user to the server, and is a device or software that has the function of transferring data via a network.

[0239] A "draft generation means" is a device or software that has the function of automatically creating a draft of a contract or approval document based on input information.

[0240] A "terminal" is a device used by a user to input contract information and approval information and to review and revise drafts, and specifically includes smartphones, tablets, PCs, etc.

[0241] The "modification means" is a means by which the user can make necessary modifications to the generated draft, and is a device or software that allows the user to edit and change information.

[0242] The "final contract generation means" is a device or software that has the function of generating a final contract based on the revised draft.

[0243] The "means of provision" refers to the means for providing the generated final contract or request form to the user, and specifically includes providing a download link or sending it by email.

[0244] "Automation means" refers to a means for inputting contract information and approval request information using a smartphone and automatically generating contracts and approval requests using an AI model.

[0245] The "downloading means" is a means for allowing users to download the generated final contract or approval document in PDF format.

[0246] This invention is a system that automates the process of creating contracts and approval documents, and aims to generate documents efficiently and accurately by linking a smartphone with a server. To implement this invention, the following system configuration and software are used.

[0247] System Configuration

[0248] 1. Input method:

[0249] A user inputs contract information and approval information using a smartphone. The application on the smartphone provides a form for the user to input.

[0250] 2. Means of transmission:

[0251] The application installed on the smartphone sends the entered contract information and approval information to the server in JSON format.

[0252] 3. Draft generation method:

[0253] The server analyzes the received contract and approval information and generates optimal contract and approval drafts using an NLP (natural language processing)-based generative AI model that runs on a machine learning framework such as TENSORFLOW®.

[0254] 4. Means of transmission:

[0255] The server then sends the generated draft to the smartphone in JSON format.

[0256] 5. Remedies:

[0257] Users can check the contract draft and approval draft on their smartphone and make any necessary revisions, which are then sent back to the server.

[0258] 6. Final contract generation means:

[0259] The server then generates the final contract and approval document, reflecting the changes. This process also utilizes the generative AI model.

[0260] 7. Means of provision:

[0261] The final contract and approval document will be made available for download by the user in PDF format.

[0262] Specific examples

[0263] As a concrete example, consider a case where a user enters the following information into a smartphone app: "Contract partner: a certain company, Contract details: product sales, Contract amount: 1 million yen, Contract expiration date: December 31, 2023." Once this information is entered, the app automatically sends the data to the server and generates a draft based on it. The user reviews the draft and corrects the "Contract amount" to "1.2 million yen," after which the final contract is generated and can be downloaded in PDF format.

[0264] Example of an input prompt for a generative AI model:

[0265] Based on the contract information entered by the user, the appropriate contract template is selected and a draft contract is generated that includes the following information:

[0266] 1. Contracting Party: A company

[0267] 2. Contents of the Agreement: Sale of Products

[0268] 3. Contract amount: 1 million yen

[0269] 4. Contract deadline: December 31, 2023

[0270] This invention will significantly streamline the process of creating contracts and approval documents, reducing input errors, applying standardized formats, and enabling faster electronic payment services.

[0271] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0272] Step 1:

[0273] The user uses a smartphone to input contract information and approval information. Specifically, they enter information such as the contracting party, contract content, contract amount, contract deadline, etc. into an input form. This input data is converted into JSON format.

[0274] Step 2:

[0275] The terminal sends the entered contract information and approval request information to the server. Specifically, it sends JSON format data to the server via an HTTP POST request. The input data is received on the server side.

[0276] Step 3:

[0277] The server analyzes the contract information and approval request information it receives and uses a generative AI model to generate a contract draft and approval request draft. Specifically, it uses an NLP (natural language processing)-based template modeler to select an appropriate template and automatically generate the draft. This generation process uses machine learning frameworks such as TensorFlow. The input is the contract information and approval request information, and the output is the generated draft.

[0278] Step 4:

[0279] The server sends the generated contract draft and approval document draft to the terminal. The draft is converted back to JSON format and sent to the terminal via HTTP POST or WebSocket communication. The data is received on the terminal side.

[0280] Step 5:

[0281] The user checks the contract draft and the approval request draft on their device and makes any necessary revisions. Specifically, they edit the wording and conditions in the draft and confirm the revisions. This revision data is also converted to JSON format.

[0282] Step 6:

[0283] The terminal sends the revised contract draft and approval draft to the server again. This data is sent to the server in JSON format via an HTTP POST request. The revised data is received on the server side.

[0284] Step 7:

[0285] The server reflects the revisions and generates the final contract and approval document. The generative AI model is then used again to automatically generate the final document reflecting the revisions. The input is the revised data, and the output is the final contract and approval document.

[0286] Step 8:

[0287] The server provides the final contract and approval document to the user through a delivery method. Specifically, the final document generated in PDF format is provided as a download link. It can also be sent by email if necessary. The input is the final document, and the output is a download link or email.

[0288] 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.

[0289] The present invention combines a system that automates the process of creating contracts and approval documents with an emotion engine that recognizes the user's emotions and adjusts the document content based on those emotions. Specific embodiments for implementing the program for this system are described below.

[0290] System Overview

[0291] This system allows users to input contract and approval information using a terminal, and then sends that information to a server, which then automatically generates drafts of the contract and approval documents and provides the final documents. Furthermore, the system has the ability to recognize the user's emotions using an emotion engine and adjust the document content accordingly.

[0292] Contract Creation Process

[0293] 1. The user enters the contract information using the terminal.

[0294] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount." At that time, the device's camera and microphone are used to analyze the user's facial expressions and voice, and emotional data is also collected.

[0295] 2. The device sends the data to the server

[0296] The terminal converts the entered contract information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[0297] 3. The server generates a draft contract

[0298] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information and emotion data.

[0299] 4. The server adjusts the draft based on the sentiment data.

[0300] The server adjusts the content of the generated contract draft based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it may emphasize important contract terms or insert additional explanations.

[0301] 5. User reviews and edits the draft

[0302] The user checks the draft contract displayed on the device and makes any necessary changes, such as amending the contract amount or adding payment terms. Emotional data is collected again during this process.

[0303] 6. The device sends the correction data and emotion data to the server.

[0304] The device transmits the user's corrections and the re-collected emotion data to the server.

[0305] 7. The server generates the final contract

[0306] The server generates a final contract based on the amendments and emotion data, and the final contract is saved and provided as a PDF file or other document format.

[0307] 8. Provision of the Final Agreement

[0308] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[0309] Approval document drafting process

[0310] 1. The user enters the approval information based on the contract information

[0311] The user reviews the final contract on the terminal, then enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval. Emotional data is also collected in the same way.

[0312] 2. The device sends the data to the server

[0313] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[0314] 3. The server generates a draft request.

[0315] The server stores the received approval information in a database and uses it as input for an AI model, which selects the most appropriate approval document template based on the approval information and emotion data.

[0316] 4. The server adjusts the draft based on the sentiment data.

[0317] The server adjusts the content of the generated draft request form based on the analysis results of the emotion engine. For example, if the user feels anxious, it adds a supplementary explanation to the risk assessment section.

[0318] 5. User reviews and edits the draft

[0319] The user checks the draft approval document displayed on the device and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotional data is collected again during this process.

[0320] 6. The device sends the correction data and emotion data to the server.

[0321] The device transmits the user's corrections and the re-collected emotion data to the server.

[0322] 7. The server generates the final approval document

[0323] The server generates a final approval document that reflects the corrections based on the correction data and emotion data. The generated final approval document is saved and provided as a PDF file or other document format.

[0324] 8. Providing the final approval document

[0325] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[0326] Specific examples

[0327] Specific examples of contract creation

[0328] 1. The user looks a little anxious as he enters the following information: "Contracting party: Company A, Contract details: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[0329] 2. The device sends the contract information and emotion data to the server.

[0330] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of Service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds, in emphasis, "Details of penalties regarding delivery delays" to reduce user anxiety.

[0331] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[0332] 5. The device sends the corrections and new emotion data to the server.

[0333] 6. The server finally generates the final contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[0334] Specific examples of drafting approval documents

[0335] 1. The user looks a little nervous as he enters the approval request information, such as "Purpose: provision of Service B, Contract partner: Company A, Budget: 2 million yen, Risk: Medium."

[0336] 2. The device sends these data and emotion data to the server.

[0337] 3. The server generates a draft approval document with the following specifications: "Objective: Provision of Service B, Contract Partner: Company A, Budget: 2 million yen, Risk: Medium" and adds a detailed analysis of the expected budget achievement to ease the user's tension.

[0338] 4. The user reviews the draft and corrects the "Budget" to "2.2 million yen."

[0339] 5. The device sends the corrections and new emotion data to the server.

[0340] 6. The server finally generates a final approval document with the following specifications: "Purpose: Provision of Service B, Contract Partner: Company A, Budget: 2.2 million yen, Risk: Medium" and provides it as a PDF file.

[0341] The above is a specific example of the operation of the embodiment of the present invention. This system makes it possible to create contracts and approval documents that take into account the user's emotions, thereby achieving more accurate and efficient business operations.

[0342] The processing flow will be explained below.

[0343] Contract Creation Process

[0344] Step 1:

[0345] The user opens the contract creation page on their device and accesses the new contract creation form. They enter the necessary information, such as the "contract date and time," "contract partner," "contract details," and "amount." While they are entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[0346] Step 2:

[0347] The terminal converts the entered contract information and emotional data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotional data includes emotions (e.g., joy, anxiety, surprise, etc.) analyzed from the user's facial expressions and voice.

[0348] Step 3:

[0349] The server stores the received contract information and emotion data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate contract template.

[0350] Step 4:

[0351] The server uses the AI ​​model to insert contract information into the selected template and generate a draft contract. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, it will emphasize or add additional explanations to specific parts of the contract (e.g., payment terms, delivery date).

[0352] Step 5:

[0353] The server sends a draft contract that has been adjusted based on the emotion data to the terminal. The user reviews the draft and makes any necessary changes, such as modifying the contract amount or adding payment terms. Emotion data continues to be collected even during the changes.

[0354] Step 6:

[0355] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[0356] Step 7:

[0357] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final contract, which is then saved as a document (e.g., PDF).

[0358] Step 8:

[0359] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[0360] Approval document drafting process

[0361] Step 1:

[0362] The user checks the contract on the device and then moves to a page for creating a request for approval. The user enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into the request for approval form. While the user is entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[0363] Step 2:

[0364] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotion data includes emotions (e.g., anger, anxiety, joy, etc.) analyzed from the user's facial expressions and voice.

[0365] Step 3:

[0366] The server stores the received approval information and emotion data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate approval template.

[0367] Step 4:

[0368] The server uses the AI ​​model to insert the request information into the selected template and generate a draft request document. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, adds further explanations or supporting materials to the risk assessment section.

[0369] Step 5:

[0370] The server sends a draft of the approval document, adjusted based on the emotion data, to the terminal. The user reviews the draft and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotion data continues to be collected even during the corrections.

[0371] Step 6:

[0372] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[0373] Step 7:

[0374] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final approval document, which is then saved as a document (e.g., PDF).

[0375] Step 8:

[0376] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[0377] Example 2

[0378] 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."

[0379] The traditional process of creating contracts and approval documents involves a lot of manual input and correction, which is not only time-consuming and labor-intensive, but also makes it difficult to flexibly adjust the content of the document while taking into account the user's emotions.In addition, when users are in a situation where they feel anxious or stressed, they may not be able to properly understand the content of the document, which can result in incomplete contracts or approval documents.

[0380] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting contract information, a data collection means for collecting user emotion data, a transmission means for transmitting the input contract information and emotion data to the server, a draft generation means for generating a contract draft based on the input contract information in the server, an adjustment means for adjusting the contract draft generated based on the emotion data, a transmission means for transmitting the generated contract draft to the terminal, a correction means for the user to correct the contract draft, a transmission means for transmitting the corrected contract draft and the emotion data to the server, a final contract generation means for generating a final contract reflecting the corrections, and a provision means for providing the generated final contract. This enables the generation and adjustment of documents taking the user's emotions into consideration, thereby realizing a more accurate and efficient process for creating contracts and approval requests.

[0381] "Contract information" refers to information that the user inputs as necessary information for creating a contract, and specifically includes the date and time of the contract, the contracting party, the contract contents, the contract amount, and the like.

[0382] "Emotion data" is data that indicates the psychological state of the user, obtained by analyzing the user's facial expressions and voice, and refers to emotions such as anxiety, relief, and tension that the user expressed during the input task.

[0383] "Input means" refers to an interface for a user to input contract information into a terminal, and includes input devices such as a keyboard, a mouse, and a touch screen.

[0384] The "data collection means" refers to a means for collecting user emotional data, and includes a function for capturing the user's facial expressions and voice using the device's camera and microphone, and analyzing them using an emotion recognition engine.

[0385] "Transmission means" refers to the communication protocol for transmitting the entered contract information and emotion data to the server, and mainly includes secure communication means such as HTTPS.

[0386] "Draft generation means" refers to a means for automatically generating a draft of a contract based on contract information entered into the server, and uses a generation AI model.

[0387] "Adjustment means" refers to means for adjusting the content of the contract draft generated based on emotional data, and includes a function for optimizing the content and expression of the document according to the user's emotional state.

[0388] The "modification means" is an interface that allows the user to check the contract draft and modify it as necessary, and has the function of allowing text to be added or changed.

[0389] "Means for generating a final contract" refers to means for generating a final contract based on a revised draft contract, and includes a function for saving the final contract in a document format such as PDF.

[0390] "Means of provision" refers to the means for providing the generated final contract to the user, and includes methods such as generating a download link or notifying the user by email.

[0391] The present invention relates to a system for automating the process of creating contracts and approval documents and adjusting the content of the documents by analyzing user sentiment. The system includes the following components:

[0392] Hardware and Software Configuration

[0393] 1. Terminal

[0394] Input means: Provide an interface for users to input contract information using a keyboard, mouse, touch screen, etc.

[0395] Data collection method: The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice. The emotion recognition engine used is, for example, Microsoft® Azure® Emotion API.

[0396] Transmission method: The collected contract information and emotion data are converted into JSON format and sent to the server via the HTTPS protocol.

[0397] 2. Server

[0398] Draft generation means: The server stores the received contract information in a database (e.g., MySQL (registered trademark)) and generates a contract draft using a generative AI model such as OpenAI (registered trademark)'s GPT-4 (registered trademark).

[0399] Adjustment: The content of the generated draft contract is adjusted based on the sentiment data, such as emphasizing important points in the contract or adding additional explanations if the user feels uneasy.

[0400] Final contract generation method: Generate a final contract based on the revised draft contract. The final contract is saved in PDF format (e.g., by converting it to PDF format using the PyPDF2 library).

[0401] Provision method: A download link for the generated final contract is generated and provided to the user's device.

[0402] Specific examples

[0403] Specific examples of contract creation

[0404] 1. The user looks a little uneasy when entering the following information: "Contract partner: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[0405] 2. The device sends the contract information and emotion data to the server.

[0406] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds "Details of penalties regarding delivery delays" in an emphasised manner to reduce the user's concerns.

[0407] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[0408] 5. The device sends the corrections and new emotion data to the server.

[0409] 6. The server finally generates the final contract with the following details: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[0410] Specific examples of drafting approval documents

[0411] 1. The user looks a little nervous as he enters the approval request information, such as "Purpose: provision of Service B, Contract partner: Company A, Budget: 2 million yen, Risk: Medium."

[0412] 2. The device sends these data and emotion data to the server.

[0413] 3. The server generates a draft approval document with the following specifications: "Objective: Provision of Service B, Contracting Party: Company A, Budget: 2 million yen, Risk: Medium" and adds a detailed analysis of the expected budget achievement to ease the user's tension.

[0414] 4. The user reviews the draft and corrects the "Budget" to "2.2 million yen."

[0415] 5. The device sends the corrections and new emotion data to the server.

[0416] 6. The server finally generates a final approval document with the following criteria: "Purpose: Provision of Service B, Contracting Party: Company A, Budget: 2.2 million yen, Risk: Medium" and provides it as a PDF file.

[0417] Prompt Sentence Examples

[0418] Contract drafting prompt examples

[0419] "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[0420] Example prompts for creating approval documents

[0421] "Objective: Provision of Service B, Contractor: Company A, Budget: 2 million yen, Risk: Medium."

[0422] The above is an embodiment of the present invention. This system makes it possible to create contracts and approval documents that take the user's emotions into consideration, thereby achieving more accurate and efficient business operations.

[0423] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0424] Step 1:

[0425] The user inputs the contract information into the terminal. The user then inputs information such as "contract partner," "contract details," "contract amount," and "contract term" into the provided contract creation form. The input information is stored in the terminal as contract information data.

[0426] Step 2:

[0427] The device collects emotion data. The device uses a camera to capture the user's facial expressions and a microphone to collect voice data. This data is analyzed by an emotion recognition engine (e.g., Microsoft Azure Emotion API) and stored on the device as the user's emotion data.

[0428] Step 3:

[0429] The device sends the contract information and emotion data to the server. The device converts the contract information and emotion data into JSON format and sends it to the server using the HTTPS protocol. After the input data reaches the server, it is stored in a database.

[0430] Step 4:

[0431] The server generates a contract draft. Based on the received contract information, the server uses a generative AI model (e.g., GPT-4) to create a prompt sentence. The server inputs this prompt sentence into the AI ​​model, selects the most appropriate contract template, and generates a contract draft. The generated draft is saved on the server as draft data.

[0432] Step 5:

[0433] The server adjusts the contract draft based on the emotion data. The server adjusts the content of the draft data based on the analysis results of the emotion recognition engine. Specifically, if the user feels uneasy, the server emphasizes important points in the contract or inserts additional explanations. The adjusted draft is saved on the server as adjusted draft data.

[0434] Step 6:

[0435] The server sends the contract draft to the terminal, and the server sends the adjusted draft data to the terminal, and the terminal displays the received data and provides it to the user.

[0436] Step 7:

[0437] The user checks and amends the contract draft. The user checks the displayed contract draft and makes any necessary amendments. The amended data is saved on the terminal as amended draft data.

[0438] Step 8:

[0439] The device sends the revised draft data and emotion data to the server. The device converts the revised draft data and the re-collected emotion data into JSON format and sends it to the server using the HTTPS protocol. The sent data is stored on the server.

[0440] Step 9:

[0441] The server generates the final contract. The server generates the final contract based on the revised draft data and emotion data. The final contract is generated in PDF format (e.g., using the PyPDF2 library) and saved on the server as final contract data.

[0442] Step 10:

[0443] The server provides the final contract to the user. The server generates a download link for the final contract and sends it to the user's device. The user downloads the final contract through the device and saves it as needed.

[0444] The above process enables automatic generation and adjustment of contracts that take the user's feelings into consideration, realizing efficient and accurate contract creation.

[0445] (Application example 2)

[0446] 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."

[0447] In the process of creating contracts and approval documents, conventional methods require users to spend a lot of time entering and editing information, and do not take emotional states into consideration, resulting in problems of reduced efficiency and accuracy. Furthermore, in-store contract work requires particularly quick responses, which makes it necessary to reduce the emotional stress of users. To solve these issues, a system is needed that recognizes users' emotional data and automatically adjusts the content of contracts and approval documents based on that data.

[0448] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0449] In this invention, the server includes input means for inputting contract information, transmission means for transmitting the input contract information to the server, draft generation means for generating a contract draft on the server based on the input contract information, transmission means for transmitting the generated contract draft to the terminal, modification means for the user to modify the contract draft, transmission means for transmitting the modified contract draft to the server, final contract generation means for generating a final contract reflecting the modifications, provision means for providing the generated final contract, and emotion recognition means for recognizing user emotion data from a camera or microphone of the terminal and adjusting the content of the contract draft based on the emotion data. This makes it possible to efficiently and accurately create contracts and approval documents while taking the user's emotions into consideration.

[0450] The "input means" is a means for the user to input contract information into the terminal.

[0451] The "transmission means" is a means for the terminal to transmit the input contract information and the revised contract draft to the server.

[0452] The "draft generation means" is a means for the server to generate a contract draft based on the contract information input.

[0453] The "modification means" is a means by which the user can check the generated contract draft and modify it as necessary.

[0454] The "final contract generation means" is a means for generating a final contract based on the revised contract draft.

[0455] The "provision means" is a means for providing the generated final contract to the terminal.

[0456] The "emotion recognition means" is a means for recognizing the user's emotion data using the camera or microphone of the terminal and analyzing the data.

[0457] The present invention provides a system for improving the efficiency of the process of creating contracts and approval documents, and automatically generating documents that reflect the user's feelings. Specific embodiments for carrying out the present invention will be described below.

[0458] System Overview

[0459] This system allows users to input contract and approval information using a terminal, and then automatically generates drafts of the contract and approval documents by sending the information and emotional data to a server, which then provides the final documents after the user has confirmed and corrected them.The system uses the terminal's camera and microphone to recognize and analyze the emotional data.

[0460] Hardware and Software Configuration

[0461] The system includes the following hardware and software:

[0462] Terminal: Equipped with a camera and microphone for users to input contract information and collect emotional data.

[0463] Server: Generates drafts and final documents of contracts and approval documents.

[0464] Emotion Recognition Software: Software that analyzes a user's facial expressions and voice to obtain emotional data (e.g., "FaceAPI").

[0465] Machine learning models: Generative AI models (e.g., "GPT-4") for generating draft contracts and approval documents.

[0466] Data processing and calculation

[0467] 1. Enter and submit contract information:

[0468] The user enters contract information (e.g., contract date, contract partner, contract details, and amount) into a form on the device. The entered data, along with emotion data captured by the device's camera and microphone, is converted into JSON format and sent to the server using the HTTPS protocol.

[0469] 2. Draft generation and reflection of sentiment data:

[0470] The server stores the received contract information and emotion data in a database and uses them as input for a machine learning model. The generative AI model generates an optimal contract draft based on this data and adjusts the content using emotion recognition. For example, if the user is feeling anxious, the draft content is adjusted to emphasize important terms or additional explanations.

[0471] 3. Review and revise the draft:

[0472] The generated contract draft is sent to the terminal and confirmed by the user. The user then modifies the contract draft as necessary and sends the modifications and new emotion data back to the server.

[0473] 4. Generation and Delivery of Final Agreement:

[0474] The server generates the final contract based on the correction data and emotion data and provides it to the terminal. The final contract can then be downloaded in PDF format or other formats.

[0475] Specific examples

[0476] 1. Examples of contract drafting:

[0477] The user enters "Contract partner: Product Supply Co., Ltd., Contract content: Purchase of Product A, Contract amount: 500,000 yen, Contract expiration date: December 31, 2023."

[0478] Facial expression analysis determined that the user was slightly anxious.

[0479] The server generates a draft contract with the following terms: "Product Supply Co., Ltd., Procurement of Product A, Contract Amount: 500,000 yen, Contract Term: December 31, 2023," and emphasizes "detailed penalty conditions for delivery delays" to reduce anxiety.

[0480] The user checks the draft and corrects the "Contract Expiration Date" to "January 31, 2024."

[0481] The server finally creates a final contract stating "Product Supply Co., Ltd., Purchase of Product A, Contract Amount: 500,000 yen, Contract Expiry: January 31, 2024" and provides it as a PDF file.

[0482] 2. Example of drafting a request for approval:

[0483] The user enters "Purchase of Product A, Contract partner: Product Supply Co., Ltd., Budget: 500,000 yen, Risk: Medium."

[0484] Camera analysis determined that the user was in a tense state.

[0485] The server generates a draft approval document with the following specifications: "Objective: Procurement of Product A, Contractor: Product Supply Co., Ltd., Budget: 500,000 yen, Risk: Medium," and details the expected budget achievement to ease tension.

[0486] The user checks the draft and corrects the "Budget" to "550,000 yen."

[0487] The server finally creates a final approval document with the following description: "Purchase of Product A, Contractor: Product Supply Co., Ltd., Budget: 550,000 yen, Risk: Medium" and provides it as a PDF file.

[0488] Prompt Sentence Examples

[0489] Example prompts used to generate a draft contract:

[0490] Generate a draft agreement with the following contract information:

[0491] Counterparty: Product Supply Co., Ltd.

[0492] Contract details: Purchase of product A

[0493] Contract amount: 500,000 yen

[0494] User sentiment data supplement: The user appears anxious, so include additional explanations about important terms and conditions.

[0495] The above is an embodiment of the invention. This system makes it possible to create contracts and approval documents efficiently and accurately, taking into account the user's emotions.

[0496] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0497] Step 1:

[0498] Enter and send contract information and emotion data

[0499] The user uses a terminal to input contract information (contract date, contract partner, contract content, amount, etc.). The terminal collects this input data and also uses a camera and microphone to obtain the user's emotional data (facial expressions, tone of voice, etc.). This contract information and emotional data are converted into JSON format and sent to the server using the HTTPS protocol. The input is manual input by the user, and the output is JSON data sent to the server.

[0500] Step 2:

[0501] Emotion recognition and contract draft generation

[0502] The server stores the received contract information and emotional data in a database. It then analyzes the emotional data using emotion recognition software (e.g., FaceAPI) to determine the emotional state (e.g., anxiety, relief, tension). Based on the analysis results, the server uses a machine learning model (e.g., GPT-4) to generate an optimal contract draft. The server's input is JSON data, and its output is the initial contract draft.

[0503] Step 3:

[0504] Adjusting contract drafts using sentiment data

[0505] The server uses the analysis results of the emotion recognition software to adjust the content of the generated draft contract. If the user feels uneasy, it makes corrections such as highlighting important contract terms or inserting additional explanations into the draft contract. The input is the analysis results of the emotion recognition software and the draft contract, and the output is the adjusted draft contract.

[0506] Step 4:

[0507] Sending and reviewing a draft agreement

[0508] The terminal receives the adjusted contract draft and displays it to the user. The user checks the draft and makes any necessary corrections. After entering the corrections, the user sends the revised draft back to the server. The input is the corrections from the user, and the output is the revised contract draft.

[0509] Step 5:

[0510] Reflecting amendments and generating the final contract

[0511] The server receives the revised contract draft, reviews its contents again taking into account the emotional data, generates the final contract, and saves it in a format such as PDF. The input is the revised contract draft and the emotional data, and the output is the final contract.

[0512] Step 6:

[0513] Provision of final contract

[0514] The server generates a download link to provide the final contract to the terminal. The user downloads and saves the final contract through this link. The input is the final contract, and the output is the download link.

[0515] 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.

[0516] 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.

[0517] 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.

[0518] [Second embodiment]

[0519] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0520] 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.

[0521] 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).

[0522] 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.

[0523] 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.

[0524] 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).

[0525] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0526] 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.

[0527] 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.

[0528] 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.

[0529] In the smart glasses 214, 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.

[0530] 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."

[0531] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments for implementing the program of this system will be described below.

[0532] System Overview

[0533] In this system, users use a terminal to input contract information and approval information, and then send that information to a server, which then automatically generates a draft of the contract or approval document and provides the final document.

[0534] Contract Creation

[0535] 1. The user enters the contract information using the terminal.

[0536] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount," and then indicates completion of input.

[0537] 2. The device sends the data to the server

[0538] The terminal sends the entered contract information to the server in a data format (e.g., JSON).

[0539] 3. The server generates a draft contract

[0540] The server analyzes the received contract information, selects an appropriate contract template using an AI model (e.g., an NLP-based template modeler), and automatically generates a contract draft. The generated draft is then converted back into a data format and sent to the terminal.

[0541] 4. User checks and edits the draft

[0542] The user can check the draft contract on the terminal and make any necessary changes, such as modifying the "contracting party information" or adding "payment terms."

[0543] 5. The device sends the correction data to the server

[0544] The terminal transmits the user's modifications to the server again.

[0545] 6. The server generates the final contract

[0546] The server generates a final version of the contract that reflects the amendments and provides it as a document such as a PDF file, which the user can download.

[0547] Drafting approval documents

[0548] 1. The user enters the approval information based on the contract information

[0549] The user reviews the final contract on the terminal and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval.

[0550] 2. The device sends the data to the server

[0551] The terminal transmits the input approval information to the server in data format.

[0552] 3. The server generates a draft request.

[0553] The server analyzes the received approval information, selects an appropriate approval template based on the AI ​​model, and automatically generates a draft approval document, which is then sent to the device.

[0554] 4. User checks and edits the draft

[0555] The user can review the draft approval document on their device and make any necessary corrections, such as changing the "budget details" or adding comments for the "risk assessment."

[0556] 5. The device sends the correction data to the server

[0557] The terminal transmits the user's modifications to the server again.

[0558] 6. The server generates the final approval document

[0559] The server generates a final version of the approval document that reflects the revisions and provides it as a document such as a PDF file, which the user can download.

[0560] Specific examples

[0561] Specific examples of contract creation

[0562] 1. The user enters the following: "Contract partner: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[0563] 2. The device sends this contract information to the server.

[0564] 3. The server generates a draft contract with the following information: "Contracting party: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[0565] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[0566] 5. The device sends the modifications to the server.

[0567] 6. The server finally generates the final contract with the following content: "Contract details: Sales of Product Y, Contract amount: 5 million yen, Contract expiration date: January 31, 2026" and provides it as a PDF file.

[0568] Specific examples of drafting approval documents

[0569] 1. The user enters approval information such as "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[0570] 2. The device sends this data to the server.

[0571] 3. The server generates a draft approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[0572] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[0573] 5. The device sends the modifications to the server.

[0574] 6. The server finally generates the final approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[0575] The above is a specific example of the operation of the embodiment of the present invention. This system improves the efficiency of the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[0576] The processing flow will be explained below.

[0577] Contract Creation Process

[0578] Step 1:

[0579] The user opens the contract creation page on their device and accesses the new contract creation form. The user enters the necessary information, such as the "contract date and time," "contract partner," "contract content," and "amount."

[0580] Step 2:

[0581] The terminal converts the entered contract information into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[0582] Step 3:

[0583] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information.

[0584] Step 4:

[0585] The server uses the AI ​​model to insert the contract information into the selected template and generate a draft contract, which is then converted back into a data format and sent to the device.

[0586] Step 5:

[0587] The user checks the draft contract displayed on the terminal and makes any necessary corrections, such as amending the contract amount or adding payment terms.

[0588] Step 6:

[0589] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[0590] Step 7:

[0591] The server generates the final contract based on the revised data, and saves the final contract as a PDF file or other document format.

[0592] Step 8:

[0593] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[0594] Approval document drafting process

[0595] Step 1:

[0596] The user checks the contract on their device and then moves to the page for creating a request for approval. The user enters information for the request, such as the purpose of the contract, the contracting party, the budget, and risk assessment, into the request for approval creation form.

[0597] Step 2:

[0598] The terminal converts the input approval information into a comprehensive data format (e.g., JSON) and sends it to the server, using the HTTPS protocol to ensure data security.

[0599] Step 3:

[0600] The server stores the received approval information in a database and uses it as input for the AI ​​model, which selects the most appropriate approval document template based on the approval information.

[0601] Step 4:

[0602] The server uses the AI ​​model to insert the approval request information into the selected template and generate a draft of the approval request document, which is then converted back into a data format and sent to the device.

[0603] Step 5:

[0604] The user checks the draft approval document displayed on the terminal and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments."

[0605] Step 6:

[0606] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[0607] Step 7:

[0608] The server generates a final approval document that reflects the corrections based on the corrected data, and saves the final approval document as a PDF file or other document format.

[0609] Step 8:

[0610] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[0611] Example 1

[0612] 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."

[0613] The traditional process for creating contracts and approval documents involves a lot of manual data entry, document generation, and editing, which results in low work efficiency and a high likelihood of problems due to input errors and inconsistent formats.In addition, it is difficult to standardize various documents, which can easily lead to variations in quality.

[0614] 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.

[0615] In this invention, the server includes input means for inputting contract data, transmission means for transmitting the input contract data to an information processing device, draft generation means for generating a contract draft based on the input contract data in the information processing device, transmission means for transmitting the generated contract draft to a terminal, correction means for the user to correct the contract draft, transmission means for transmitting the corrected contract draft to the information processing device, final contract generation means for generating a final contract reflecting the corrections, provision means for providing the generated final contract document, and means for using a generative AI model. This automates the process of creating contracts and approval documents, reducing input errors, improving work efficiency, and enabling the application of standardized formats.

[0616] "Input means" refers to a device or function that provides an interface for users to manually input contract data and approval data.

[0617] The "transmission means" is a communication device or function for transmitting data obtained by the input means to an information processing device or a server.

[0618] The "draft generation means" is a processing function or program for automatically generating a draft of a contract document or approval document based on the received data.

[0619] The "modification means" is a device or function that provides an interface for a user to check the generated draft of the contract document or approval document and modify the content as necessary.

[0620] The "final contract document generation means" is a processing function or program for generating a final contract document or approval document that reflects the corrections incorporated by the correction means.

[0621] The "means for providing" is a device or function for providing the generated final contract document or final approval document in a form that can be used by the user.

[0622] A "generative AI model" is an algorithm or system that uses machine learning techniques to select appropriate templates based on received data and automatically generate documents.

[0623] An "information processing device" is a computer or server that processes input data and provides various functions such as document generation.

[0624] A "terminal" is a device such as a personal computer, tablet, or smartphone that a user uses to enter contract information and approval information and to review and modify generated documents.

[0625] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments of this system will be described below.

[0626] Hardware and software used

[0627] Hardware: User devices (personal computers, tablets, smartphones, etc.), servers (high-performance computers)

[0628] Software: Web forms (front-end), server-side generative AI models (e.g., NLP-based template modelers)

[0629] System Overview

[0630] In this system, users input contract data and approval data using a terminal and send the information to a server, which then automatically generates draft contract and approval documents and provides the final documents. This streamlines the document creation process, reduces input errors, and enables the application of standardized formats.

[0631] Contract Creation Process

[0632] 1. The user enters the contract data using the terminal.

[0633] The user accesses the contract creation form using a web browser or a dedicated application, enters information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and clicks the "send" button.

[0634] 2. The device sends the data to the server

[0635] The terminal compiles the contract information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[0636] 3. The server generates a draft contract

[0637] The server parses the received JSON data and extracts the contract information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[0638] 4. User checks and edits the draft

[0639] The user can check the draft contract displayed on the terminal and modify it as necessary. For example, they can add information about the contracting party or modify the contract expiration date.

[0640] 5. The device sends the correction data to the server

[0641] The terminal sends the revised contract information again to the server in JSON format.

[0642] 6. The server generates the final contract

[0643] The server generates a final version of the contract that reflects the amendments, generates the final contract as a PDF document, and provides a link for the user to download it.

[0644] Approval document drafting process

[0645] 1. The user enters the approval request data based on the contract information

[0646] The user accesses the approval request creation form using a web browser or a dedicated application, reviews the final contract, and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment based on the contract's contents.

[0647] 2. The device sends the data to the server

[0648] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[0649] 3. The server generates a draft request.

[0650] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[0651] 4. User checks and edits the draft

[0652] The user can review the draft of the approval document displayed on the terminal and make corrections as necessary, for example, by changing the "budget details" or adding comments for the "risk assessment."

[0653] 5. The device sends the correction data to the server

[0654] The terminal sends the corrected approval information back to the server in JSON format.

[0655] 6. The server generates the final approval document

[0656] The server generates a final version of the approval document that reflects the changes, generates the final approval document as a PDF document, and provides a link for the user to download it.

[0657] Specific examples

[0658] Specific examples of contract creation

[0659] 1. The user enters the following information: "Contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[0660] 2. The device sends this contract information to the server.

[0661] 3. The server generates a draft contract with the following specifications: "Contracting party: a certain company, Contract content: product sales, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[0662] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[0663] 5. The device sends the modifications to the server.

[0664] 6. The server finally generates the final contract with the following content: "Contract details: product sales, contract amount: 5 million yen, contract expiration date: January 31, 2026" and provides it as a PDF file.

[0665] Specific examples of drafting approval documents

[0666] 1. The user enters the approval information, such as "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[0667] 2. The device sends this data to the server.

[0668] 3. The server generates a draft request form with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[0669] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[0670] 5. The device sends the modifications to the server.

[0671] 6. The server finally generates a final approval document with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[0672] As a result, the present invention streamlines the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[0673] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0674] Contract Creation Process

[0675] Step 1:

[0676] The user enters the contract data using the terminal.

[0677] The user accesses the contract creation form using a web browser or a dedicated application. They enter information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and then click the "Submit" button. The input data might include, for example, "contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[0678] Step 2:

[0679] The device sends data to the server

[0680] The terminal compiles the contract data entered by the user as JSON format data. The generated JSON data is sent to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format contract data, which is sent to the server.

[0681] Step 3:

[0682] The server generates a draft contract

[0683] The server parses the received JSON data and extracts the contract data. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract data to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated contract draft.

[0684] Step 4:

[0685] User reviews and edits the draft

[0686] The user checks the contract draft displayed on the terminal. If necessary, they modify the content, for example, adding "information about the contracting party" or modifying the "contract expiration date." The input data includes the content of the draft, especially the modified information. As a specific example of user behavior, the "contract expiration date" is modified to "January 31, 2026."

[0687] Step 5:

[0688] The device sends the correction data to the server

[0689] The terminal sends the modified contract data to the server again in JSON format. The input data contains the modified draft information, which is converted back to JSON format and provides the modified data that is sent to the server as output.

[0690] Step 6:

[0691] The server generates the final contract

[0692] The server generates a final contract that reflects the amendments. It generates the final contract as a PDF document and provides a link for the user to download it. The input data is the amended contract information, and the output is a PDF file of the final contract.

[0693] Approval document drafting process

[0694] Step 1:

[0695] The user enters approval data based on the contract information

[0696] The user accesses the approval request creation form using a web browser or a dedicated application. After reviewing the final contract, the user inputs information such as "contract purpose," "contract partner," "budget," and "risk assessment" based on the contract's contents. For example, input data might include "purpose: product sales, contract partner: certain company, budget: 5 million yen, risk: low."

[0697] Step 2:

[0698] The device sends data to the server

[0699] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format approval request data, which is sent to the server.

[0700] Step 3:

[0701] The server generates a draft request.

[0702] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated approval request draft.

[0703] Step 4:

[0704] User reviews and edits the draft

[0705] The user checks the draft approval document displayed on the terminal. If necessary, the user modifies the contents, for example, changing the "budget details" or adding a comment to the "risk assessment." The input data includes the contents of the draft, especially the modified information. As a specific example of user behavior, the user modifies the "budget" to "6 million yen."

[0706] Step 5:

[0707] The device sends the correction data to the server

[0708] The terminal sends the revised draft information to the server again in JSON format. The input data contains the revised draft information, which is converted back to JSON format and provides the revised data to be sent to the server as output.

[0709] Step 6:

[0710] The server generates the final approval document

[0711] The server generates a final version of the approval document that reflects the revisions. The final approval document is generated as a PDF document and a link is provided for users to download. The input data is the revised approval document information, and the output is a PDF file of the final approval document.

[0712] (Application example 1)

[0713] 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."

[0714] The process of creating contracts and approval documents has traditionally been done manually, resulting in time-consuming and labor-intensive processes, and the possibility of input errors and format inconsistencies. Furthermore, in situations where speedy transactions are required, such as electronic payment services, there is a growing demand for an automated system for generating contracts and approval documents that can respond smoothly and instantly. This project aims to solve these problems.

[0715] 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.

[0716] In this invention, the server includes an input means for inputting contract information, a transmission means for transmitting the input contract information to the server, a draft generation means for generating a contract draft based on the input contract information in the server, a transmission means for transmitting the generated contract draft to a terminal, a correction means for a user to correct the contract draft, a transmission means for transmitting the corrected contract draft to the server, a final contract generation means for generating a final contract reflecting the corrections, a provision means for providing the generated final contract, an automation means for inputting contract information and approval request information using a smartphone and automatically generating a contract and approval request using an AI model, and a download means for making the generated final contract and approval request request downloadable in PDF format. This significantly streamlines the process of creating contracts and approval requests, reduces input errors, enables the application of standardized formats, and enables rapid use of electronic payment services.

[0717] "Contract information" refers to information necessary to create a contract, and specifically includes information such as the contracting party, contract contents, contract amount, contract period, etc.

[0718] The "transmission means" is a means for sending information entered by the user to the server, and is a device or software that has the function of transferring data via a network.

[0719] A "draft generation means" is a device or software that has the function of automatically creating a draft of a contract or approval document based on input information.

[0720] A "terminal" is a device used by a user to input contract information and approval information and to review and revise drafts, and specifically includes smartphones, tablets, PCs, etc.

[0721] The "modification means" is a means by which the user can make necessary modifications to the generated draft, and is a device or software that allows the user to edit and change information.

[0722] The "final contract generation means" is a device or software that has the function of generating a final contract based on the revised draft.

[0723] The "means of provision" refers to the means for providing the generated final contract or request form to the user, and specifically includes providing a download link or sending it by email.

[0724] "Automation means" refers to a means for inputting contract information and approval request information using a smartphone and automatically generating contracts and approval requests using an AI model.

[0725] The "downloading means" is a means for allowing users to download the generated final contract or approval document in PDF format.

[0726] This invention is a system that automates the process of creating contracts and approval documents, and aims to generate documents efficiently and accurately by linking a smartphone with a server. To implement this invention, the following system configuration and software are used.

[0727] System Configuration

[0728] 1. Input method:

[0729] A user inputs contract information and approval information using a smartphone. The application on the smartphone provides a form for the user to input.

[0730] 2. Means of transmission:

[0731] The application installed on the smartphone sends the entered contract information and approval information to the server in JSON format.

[0732] 3. Draft generation method:

[0733] The server analyzes the received contract and approval information and generates optimal contract and approval drafts using an NLP (natural language processing)-based generative AI model that runs on a machine learning framework such as TensorFlow.

[0734] 4. Means of transmission:

[0735] The server then sends the generated draft to the smartphone in JSON format.

[0736] 5. Remedies:

[0737] Users can check the contract draft and approval draft on their smartphone and make any necessary revisions, which are then sent back to the server.

[0738] 6. Final contract generation means:

[0739] The server then generates the final contract and approval document, reflecting the changes. This process also utilizes the generative AI model.

[0740] 7. Means of provision:

[0741] The final contract and approval document will be made available for download by the user in PDF format.

[0742] Specific examples

[0743] As a concrete example, consider a case where a user enters the following information into a smartphone app: "Contract partner: a certain company, Contract details: product sales, Contract amount: 1 million yen, Contract expiration date: December 31, 2023." Once this information is entered, the app automatically sends the data to the server and generates a draft based on it. The user reviews the draft and corrects the "Contract amount" to "1.2 million yen," after which the final contract is generated and can be downloaded in PDF format.

[0744] Example of an input prompt for a generative AI model:

[0745] Based on the contract information entered by the user, the appropriate contract template is selected and a draft contract is generated that includes the following information:

[0746] 1. Contracting Party: A company

[0747] 2. Contents of the Agreement: Sale of Products

[0748] 3. Contract amount: 1 million yen

[0749] 4. Contract deadline: December 31, 2023

[0750] This invention will significantly streamline the process of creating contracts and approval documents, reducing input errors, applying standardized formats, and enabling faster electronic payment services.

[0751] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0752] Step 1:

[0753] The user uses a smartphone to input contract information and approval information. Specifically, they enter information such as the contracting party, contract content, contract amount, contract deadline, etc. into an input form. This input data is converted into JSON format.

[0754] Step 2:

[0755] The terminal sends the entered contract information and approval request information to the server. Specifically, it sends JSON format data to the server via an HTTP POST request. The input data is received on the server side.

[0756] Step 3:

[0757] The server analyzes the contract information and approval request information it receives and uses a generative AI model to generate a contract draft and approval request draft. Specifically, it uses an NLP (natural language processing)-based template modeler to select an appropriate template and automatically generate the draft. This generation process uses machine learning frameworks such as TensorFlow. The input is the contract information and approval request information, and the output is the generated draft.

[0758] Step 4:

[0759] The server sends the generated contract draft and approval document draft to the terminal. The draft is converted back to JSON format and sent to the terminal via HTTP POST or WebSocket communication. The data is received on the terminal side.

[0760] Step 5:

[0761] The user checks the contract draft and the approval request draft on their device and makes any necessary revisions. Specifically, they edit the wording and conditions in the draft and confirm the revisions. This revision data is also converted to JSON format.

[0762] Step 6:

[0763] The terminal sends the revised contract draft and approval draft to the server again. This data is sent to the server in JSON format via an HTTP POST request. The revised data is received on the server side.

[0764] Step 7:

[0765] The server reflects the revisions and generates the final contract and approval document. The generative AI model is then used again to automatically generate the final document reflecting the revisions. The input is the revised data, and the output is the final contract and approval document.

[0766] Step 8:

[0767] The server provides the final contract and approval document to the user through a delivery method. Specifically, the final document generated in PDF format is provided as a download link. It can also be sent by email if necessary. The input is the final document, and the output is a download link or email.

[0768] 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.

[0769] The present invention combines a system that automates the process of creating contracts and approval documents with an emotion engine that recognizes the user's emotions and adjusts the document content based on those emotions. Specific embodiments for implementing the program for this system are described below.

[0770] System Overview

[0771] This system allows users to input contract and approval information using a terminal, and then sends that information to a server, which then automatically generates drafts of the contract and approval documents and provides the final documents. Furthermore, the system has the ability to recognize the user's emotions using an emotion engine and adjust the document content accordingly.

[0772] Contract Creation Process

[0773] 1. The user enters the contract information using the terminal.

[0774] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount." At that time, the device's camera and microphone are used to analyze the user's facial expressions and voice, and emotional data is also collected.

[0775] 2. The device sends the data to the server

[0776] The terminal converts the entered contract information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[0777] 3. The server generates a draft contract

[0778] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information and emotion data.

[0779] 4. The server adjusts the draft based on the sentiment data.

[0780] The server adjusts the content of the generated contract draft based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it may emphasize important contract terms or insert additional explanations.

[0781] 5. User reviews and edits the draft

[0782] The user checks the draft contract displayed on the device and makes any necessary changes, such as amending the contract amount or adding payment terms. Emotional data is collected again during this process.

[0783] 6. The device sends the correction data and emotion data to the server.

[0784] The device transmits the user's corrections and the re-collected emotion data to the server.

[0785] 7. The server generates the final contract

[0786] The server generates a final contract based on the amendments and emotion data, and the final contract is saved and provided as a PDF file or other document format.

[0787] 8. Provision of the Final Agreement

[0788] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[0789] Approval document drafting process

[0790] 1. The user enters the approval information based on the contract information

[0791] The user reviews the final contract on the terminal, then enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval. Emotional data is also collected in the same way.

[0792] 2. The device sends the data to the server

[0793] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[0794] 3. The server generates a draft request.

[0795] The server stores the received approval information in a database and uses it as input for an AI model, which selects the most appropriate approval document template based on the approval information and emotion data.

[0796] 4. The server adjusts the draft based on the sentiment data.

[0797] The server adjusts the content of the generated draft request document based on the analysis results of the emotion engine. For example, if the user feels anxious, it adds a supplementary explanation to the risk assessment section.

[0798] 5. User reviews and edits the draft

[0799] The user checks the draft approval document displayed on the device and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotional data is collected again during this process.

[0800] 6. The device sends the correction data and emotion data to the server.

[0801] The device transmits the user's corrections and the re-collected emotion data to the server.

[0802] 7. The server generates the final approval document

[0803] The server generates a final approval document that reflects the corrections based on the correction data and emotion data. The generated final approval document is saved and provided as a PDF file or other document format.

[0804] 8. Providing the final approval document

[0805] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[0806] Specific examples

[0807] Specific examples of contract creation

[0808] 1. The user looks a little anxious as he enters the following information: "Contracting party: Company A, Contract details: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[0809] 2. The device sends the contract information and emotion data to the server.

[0810] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of Service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds, in emphasis, "Details of penalties regarding delivery delays" to reduce user anxiety.

[0811] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[0812] 5. The device sends the corrections and new emotion data to the server.

[0813] 6. The server finally generates the final contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[0814] Specific examples of drafting approval documents

[0815] 1. The user looks a little nervous as he enters the approval request information, such as "Purpose: provision of Service B, Contract partner: Company A, Budget: 2 million yen, Risk: Medium."

[0816] 2. The device sends these data and emotion data to the server.

[0817] 3. The server generates a draft approval document with the following specifications: "Objective: Provision of Service B, Contract Partner: Company A, Budget: 2 million yen, Risk: Medium" and adds a detailed analysis of the expected budget achievement to ease the user's tension.

[0818] 4. The user reviews the draft and corrects the "Budget" to "2.2 million yen."

[0819] 5. The device sends the corrections and new emotion data to the server.

[0820] 6. The server finally generates a final approval document with the following specifications: "Purpose: Provision of Service B, Contract Partner: Company A, Budget: 2.2 million yen, Risk: Medium" and provides it as a PDF file.

[0821] The above is a specific example of the operation of the embodiment of the present invention. This system makes it possible to create contracts and approval documents that take into account the user's emotions, thereby achieving more accurate and efficient business operations.

[0822] The processing flow will be explained below.

[0823] Contract Creation Process

[0824] Step 1:

[0825] The user opens the contract creation page on their device and accesses the new contract creation form. They enter the necessary information, such as the "contract date and time," "contract partner," "contract details," and "amount." While they are entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[0826] Step 2:

[0827] The terminal converts the entered contract information and emotional data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotional data includes emotions (e.g., joy, anxiety, surprise, etc.) analyzed from the user's facial expressions and voice.

[0828] Step 3:

[0829] The server stores the received contract information and emotion data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate contract template.

[0830] Step 4:

[0831] The server uses the AI ​​model to insert contract information into the selected template and generate a draft contract. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, it will emphasize or add additional explanations to specific parts of the contract (e.g., payment terms, delivery date).

[0832] Step 5:

[0833] The server sends a draft contract that has been adjusted based on the emotion data to the terminal. The user reviews the draft and makes any necessary changes, such as modifying the contract amount or adding payment terms. Emotion data continues to be collected even during the changes.

[0834] Step 6:

[0835] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[0836] Step 7:

[0837] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final contract, which is then saved as a document (e.g., PDF).

[0838] Step 8:

[0839] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[0840] Approval document drafting process

[0841] Step 1:

[0842] The user checks the contract on the device and then moves to a page for creating a request for approval. The user enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into the request for approval form. While the user is entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[0843] Step 2:

[0844] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotion data includes emotions (e.g., anger, anxiety, joy, etc.) analyzed from the user's facial expressions and voice.

[0845] Step 3:

[0846] The server stores the received approval information and emotion data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate approval template.

[0847] Step 4:

[0848] The server uses the AI ​​model to insert the request information into the selected template and generate a draft request document. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, adds further explanations or supporting materials to the risk assessment section.

[0849] Step 5:

[0850] The server sends a draft of the approval document, adjusted based on the emotion data, to the terminal. The user reviews the draft and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotion data continues to be collected even during the corrections.

[0851] Step 6:

[0852] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[0853] Step 7:

[0854] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final approval document, which is then saved as a document (e.g., PDF).

[0855] Step 8:

[0856] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[0857] Example 2

[0858] 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."

[0859] The traditional process of creating contracts and approval documents involves a lot of manual input and correction, which is not only time-consuming and labor-intensive, but also makes it difficult to flexibly adjust the content of the document while taking into account the user's emotions.In addition, when users are in a situation where they feel anxious or stressed, they may not be able to properly understand the content of the document, which can result in incomplete contracts or approval documents.

[0860] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting contract information, a data collection means for collecting user emotion data, a transmission means for transmitting the input contract information and emotion data to the server, a draft generation means for generating a contract draft based on the input contract information in the server, an adjustment means for adjusting the contract draft generated based on the emotion data, a transmission means for transmitting the generated contract draft to the terminal, a correction means for the user to correct the contract draft, a transmission means for transmitting the corrected contract draft and the emotion data to the server, a final contract generation means for generating a final contract reflecting the corrections, and a provision means for providing the generated final contract. This enables the generation and adjustment of documents taking the user's emotions into consideration, thereby realizing a more accurate and efficient process for creating contracts and approval requests.

[0861] "Contract information" refers to information that the user inputs as necessary information for creating a contract, and specifically includes the date and time of the contract, the contracting party, the contract contents, the contract amount, and the like.

[0862] "Emotion data" is data that indicates the psychological state of the user, obtained by analyzing the user's facial expressions and voice, and refers to emotions such as anxiety, relief, and tension that the user expressed during the input task.

[0863] "Input means" refers to an interface for a user to input contract information into a terminal, and includes input devices such as a keyboard, a mouse, and a touch screen.

[0864] The "data collection means" refers to a means for collecting user emotional data, and includes a function for capturing the user's facial expressions and voice using the device's camera and microphone, and analyzing them using an emotion recognition engine.

[0865] "Transmission means" refers to the communication protocol for transmitting the entered contract information and emotion data to the server, and mainly includes secure communication means such as HTTPS.

[0866] "Draft generation means" refers to a means for automatically generating a draft of a contract based on contract information entered into the server, and uses a generation AI model.

[0867] "Adjustment means" refers to means for adjusting the content of the contract draft generated based on emotional data, and includes a function for optimizing the content and expression of the document according to the user's emotional state.

[0868] The "modification means" is an interface that allows the user to check the contract draft and modify it as necessary, and has the function of allowing text to be added or changed.

[0869] "Means for generating a final contract" refers to means for generating a final contract based on a revised draft contract, and includes a function for saving the final contract in a document format such as PDF.

[0870] "Means of provision" refers to the means for providing the generated final contract to the user, and includes methods such as generating a download link or notifying the user by email.

[0871] The present invention relates to a system for automating the process of creating contracts and approval documents and adjusting the content of the documents by analyzing user sentiment. The system includes the following components:

[0872] Hardware and Software Configuration

[0873] 1. Terminal

[0874] Input means: Provide an interface for users to input contract information using a keyboard, mouse, touch screen, etc.

[0875] Data collection method: The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice. The emotion recognition engine used is, for example, Microsoft Azure Emotion API.

[0876] Transmission method: The collected contract information and emotion data are converted into JSON format and sent to the server via the HTTPS protocol.

[0877] 2. Server

[0878] Draft generation means: The server stores the received contract information in a database (e.g., MySQL) and generates a contract draft using a generative AI model such as OpenAI's GPT-4.

[0879] Adjustment: The content of the generated draft contract is adjusted based on the sentiment data, such as emphasizing important points in the contract or adding additional explanations if the user feels uneasy.

[0880] Final contract generation method: Generate a final contract based on the revised draft contract. The final contract is saved in PDF format (e.g., by converting it to PDF format using the PyPDF2 library).

[0881] Provision method: A download link for the generated final contract is generated and provided to the user's device.

[0882] Specific examples

[0883] Specific examples of contract creation

[0884] 1. The user looks a little uneasy when entering the following information: "Contract partner: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[0885] 2. The device sends the contract information and emotion data to the server.

[0886] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds "Details of penalties regarding delivery delays" in an emphasised manner to reduce the user's concerns.

[0887] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[0888] 5. The device sends the corrections and new emotion data to the server.

[0889] 6. The server finally generates the final contract with the following details: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[0890] Specific examples of drafting approval documents

[0891] 1. The user looks a little nervous as he enters the approval request information, such as "Purpose: provision of Service B, Contract partner: Company A, Budget: 2 million yen, Risk: Medium."

[0892] 2. The device sends these data and emotion data to the server.

[0893] 3. The server generates a draft approval document with the following specifications: "Objective: Provision of Service B, Contracting Party: Company A, Budget: 2 million yen, Risk: Medium" and adds a detailed analysis of the expected budget achievement to ease the user's tension.

[0894] 4. The user reviews the draft and corrects the "Budget" to "2.2 million yen."

[0895] 5. The device sends the corrections and new emotion data to the server.

[0896] 6. The server finally generates a final approval document with the following criteria: "Purpose: Provision of Service B, Contracting Party: Company A, Budget: 2.2 million yen, Risk: Medium" and provides it as a PDF file.

[0897] Prompt Sentence Examples

[0898] Contract drafting prompt examples

[0899] "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[0900] Example prompts for creating approval documents

[0901] "Objective: Provision of Service B, Contractor: Company A, Budget: 2 million yen, Risk: Medium."

[0902] The above is an embodiment of the present invention. This system makes it possible to create contracts and approval documents that take the user's emotions into consideration, thereby achieving more accurate and efficient business operations.

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

[0904] Step 1:

[0905] The user inputs the contract information into the terminal. The user then inputs information such as "contract partner," "contract details," "contract amount," and "contract term" into the provided contract creation form. The input information is stored in the terminal as contract information data.

[0906] Step 2:

[0907] The device collects emotion data. The device uses a camera to capture the user's facial expressions and a microphone to collect voice data. This data is analyzed by an emotion recognition engine (e.g., Microsoft Azure Emotion API) and stored on the device as the user's emotion data.

[0908] Step 3:

[0909] The device sends the contract information and emotion data to the server. The device converts the contract information and emotion data into JSON format and sends it to the server using the HTTPS protocol. After the input data reaches the server, it is stored in a database.

[0910] Step 4:

[0911] The server generates a contract draft. Based on the received contract information, the server uses a generative AI model (e.g., GPT-4) to create a prompt sentence. The server inputs this prompt sentence into the AI ​​model, selects the most appropriate contract template, and generates a contract draft. The generated draft is saved on the server as draft data.

[0912] Step 5:

[0913] The server adjusts the contract draft based on the emotion data. The server adjusts the content of the draft data based on the analysis results of the emotion recognition engine. Specifically, if the user feels uneasy, the server emphasizes important points in the contract or inserts additional explanations. The adjusted draft is saved on the server as adjusted draft data.

[0914] Step 6:

[0915] The server sends the contract draft to the terminal, and the server sends the adjusted draft data to the terminal, and the terminal displays the received data and provides it to the user.

[0916] Step 7:

[0917] The user checks and amends the contract draft. The user checks the displayed contract draft and makes any necessary amendments. The amended data is saved on the terminal as amended draft data.

[0918] Step 8:

[0919] The device sends the revised draft data and emotion data to the server. The device converts the revised draft data and the re-collected emotion data into JSON format and sends it to the server using the HTTPS protocol. The sent data is stored on the server.

[0920] Step 9:

[0921] The server generates the final contract. The server generates the final contract based on the revised draft data and emotion data. The final contract is generated in PDF format (e.g., using the PyPDF2 library) and saved on the server as final contract data.

[0922] Step 10:

[0923] The server provides the final contract to the user. The server generates a download link for the final contract and sends it to the user's device. The user downloads the final contract through the device and saves it as needed.

[0924] The above process enables automatic generation and adjustment of contracts that take the user's feelings into consideration, realizing efficient and accurate contract creation.

[0925] (Application example 2)

[0926] 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."

[0927] In the process of creating contracts and approval documents, conventional methods require users to spend a lot of time entering and editing information, and do not take emotional states into consideration, resulting in problems of reduced efficiency and accuracy. Furthermore, in-store contract work requires particularly quick responses, which makes it necessary to reduce the emotional stress of users. To solve these issues, a system is needed that recognizes users' emotional data and automatically adjusts the content of contracts and approval documents based on that data.

[0928] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0929] In this invention, the server includes input means for inputting contract information, transmission means for transmitting the input contract information to the server, draft generation means for generating a contract draft on the server based on the input contract information, transmission means for transmitting the generated contract draft to the terminal, modification means for the user to modify the contract draft, transmission means for transmitting the modified contract draft to the server, final contract generation means for generating a final contract reflecting the modifications, provision means for providing the generated final contract, and emotion recognition means for recognizing user emotion data from a camera or microphone of the terminal and adjusting the content of the contract draft based on the emotion data. This makes it possible to efficiently and accurately create contracts and approval documents while taking the user's emotions into consideration.

[0930] The "input means" is a means for the user to input contract information into the terminal.

[0931] The "transmission means" is a means for the terminal to transmit the input contract information and the revised contract draft to the server.

[0932] The "draft generation means" is a means for the server to generate a contract draft based on the contract information input.

[0933] The "modification means" is a means by which the user can check the generated contract draft and modify it as necessary.

[0934] The "final contract generation means" is a means for generating a final contract based on the revised contract draft.

[0935] The "provision means" is a means for providing the generated final contract to the terminal.

[0936] The "emotion recognition means" is a means for recognizing the user's emotion data using the camera or microphone of the terminal and analyzing the data.

[0937] The present invention provides a system for improving the efficiency of the process of creating contracts and approval documents, and automatically generating documents that reflect the user's feelings. Specific embodiments for carrying out the present invention will be described below.

[0938] System Overview

[0939] This system allows users to input contract and approval information using a terminal, and then automatically generates drafts of the contract and approval documents by sending the information and emotional data to a server, which then provides the final documents after the user has confirmed and corrected them.The system uses the terminal's camera and microphone to recognize and analyze the emotional data.

[0940] Hardware and Software Configuration

[0941] The system includes the following hardware and software:

[0942] Terminal: Equipped with a camera and microphone for users to input contract information and collect emotional data.

[0943] Server: Generates drafts and final documents of contracts and approval documents.

[0944] Emotion Recognition Software: Software that analyzes a user's facial expressions and voice to obtain emotional data (e.g., "FaceAPI").

[0945] Machine learning models: Generative AI models (e.g., "GPT-4") for generating draft contracts and approval documents.

[0946] Data processing and calculation

[0947] 1. Enter and submit contract information:

[0948] The user enters contract information (e.g., contract date, contract partner, contract details, and amount) into a form on the device. The entered data, along with emotion data captured by the device's camera and microphone, is converted into JSON format and sent to the server using the HTTPS protocol.

[0949] 2. Draft generation and reflection of sentiment data:

[0950] The server stores the received contract information and emotion data in a database and uses them as input for a machine learning model. The generative AI model generates an optimal contract draft based on this data and adjusts the content using emotion recognition. For example, if the user is feeling anxious, the draft content is adjusted to emphasize important terms or additional explanations.

[0951] 3. Review and revise the draft:

[0952] The generated contract draft is sent to the terminal and confirmed by the user. The user then modifies the contract draft as necessary and sends the modifications and new emotion data back to the server.

[0953] 4. Generation and Delivery of Final Agreement:

[0954] The server generates the final contract based on the correction data and emotion data and provides it to the terminal. The final contract can then be downloaded in PDF format or other formats.

[0955] Specific examples

[0956] 1. Examples of contract drafting:

[0957] The user enters "Contract partner: Product Supply Co., Ltd., Contract content: Purchase of Product A, Contract amount: 500,000 yen, Contract expiration date: December 31, 2023."

[0958] Facial expression analysis determined that the user was slightly anxious.

[0959] The server generates a draft contract with the following terms: "Product Supply Co., Ltd., Procurement of Product A, Contract Amount: 500,000 yen, Contract Term: December 31, 2023," and emphasizes "detailed penalty conditions for delivery delays" to reduce anxiety.

[0960] The user checks the draft and corrects the "Contract Expiration Date" to "January 31, 2024."

[0961] The server finally creates a final contract stating "Product Supply Co., Ltd., Purchase of Product A, Contract Amount: 500,000 yen, Contract Expiry: January 31, 2024" and provides it as a PDF file.

[0962] 2. Example of drafting a request for approval:

[0963] The user enters "Purchase of Product A, Contract partner: Product Supply Co., Ltd., Budget: 500,000 yen, Risk: Medium."

[0964] Camera analysis determined that the user was in a tense state.

[0965] The server generates a draft approval document with the following specifications: "Objective: Procurement of Product A, Contractor: Product Supply Co., Ltd., Budget: 500,000 yen, Risk: Medium," and details the expected budget achievement to ease tension.

[0966] The user checks the draft and corrects the "Budget" to "550,000 yen."

[0967] The server finally creates a final approval document with the following description: "Purchase of Product A, Contractor: Product Supply Co., Ltd., Budget: 550,000 yen, Risk: Medium" and provides it as a PDF file.

[0968] Prompt Sentence Examples

[0969] Example prompts used to generate a draft contract:

[0970] Generate a draft agreement with the following contract information:

[0971] Counterparty: Product Supply Co., Ltd.

[0972] Contract details: Purchase of product A

[0973] Contract amount: 500,000 yen

[0974] User sentiment data supplement: The user appears anxious, so include additional explanations about important terms and conditions.

[0975] The above is an embodiment of the invention. This system enables efficient and accurate creation of contracts and approval documents that take into account the user's emotions.

[0976] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0977] Step 1:

[0978] Enter and send contract information and emotion data

[0979] The user uses a terminal to input contract information (contract date, contract partner, contract content, amount, etc.). The terminal collects this input data and also uses a camera and microphone to obtain the user's emotional data (facial expressions, tone of voice, etc.). This contract information and emotional data are converted into JSON format and sent to the server using the HTTPS protocol. The input is manual input by the user, and the output is JSON data sent to the server.

[0980] Step 2:

[0981] Emotion recognition and contract draft generation

[0982] The server stores the received contract information and emotional data in a database. It then analyzes the emotional data using emotion recognition software (e.g., FaceAPI) to determine the emotional state (e.g., anxiety, relief, tension). Based on the analysis results, the server uses a machine learning model (e.g., GPT-4) to generate an optimal contract draft. The server's input is JSON data, and its output is the initial contract draft.

[0983] Step 3:

[0984] Adjusting contract drafts using sentiment data

[0985] The server uses the analysis results of the emotion recognition software to adjust the content of the generated draft contract. If the user feels uneasy, it makes corrections such as highlighting important contract terms or inserting additional explanations into the draft contract. The input is the analysis results of the emotion recognition software and the draft contract, and the output is the adjusted draft contract.

[0986] Step 4:

[0987] Sending and reviewing a draft agreement

[0988] The terminal receives the adjusted contract draft and displays it to the user. The user checks the draft and makes any necessary corrections. After entering the corrections, the user sends the revised draft back to the server. The input is the corrections from the user, and the output is the revised contract draft.

[0989] Step 5:

[0990] Reflecting amendments and generating the final contract

[0991] The server receives the revised contract draft, reviews its contents again taking into account the emotional data, generates the final contract, and saves it in a format such as PDF. The input is the revised contract draft and the emotional data, and the output is the final contract.

[0992] Step 6:

[0993] Provision of final contract

[0994] The server generates a download link to provide the final contract to the terminal. The user downloads and saves the final contract through this link. The input is the final contract, and the output is the download link.

[0995] 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.

[0996] 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.

[0997] 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.

[0998] [Third embodiment]

[0999] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1000] 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.

[1001] 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).

[1002] 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.

[1003] 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.

[1004] 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).

[1005] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1006] 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.

[1007] 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.

[1008] 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.

[1009] 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.

[1010] 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."

[1011] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments for implementing the program of this system will be described below.

[1012] System Overview

[1013] In this system, users use a terminal to input contract information and approval information, and then send that information to a server, which then automatically generates a draft of the contract or approval document and provides the final document.

[1014] Contract Creation

[1015] 1. The user enters the contract information using the terminal.

[1016] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount," and then indicates completion of input.

[1017] 2. The device sends the data to the server

[1018] The terminal sends the entered contract information to the server in a data format (e.g., JSON).

[1019] 3. The server generates a draft contract

[1020] The server analyzes the received contract information, selects an appropriate contract template using an AI model (e.g., an NLP-based template modeler), and automatically generates a contract draft. The generated draft is then converted back into a data format and sent to the terminal.

[1021] 4. User checks and edits the draft

[1022] The user can check the draft contract on the terminal and make any necessary changes, such as modifying the "contracting party information" or adding "payment terms."

[1023] 5. The device sends the correction data to the server

[1024] The terminal transmits the user's modifications to the server again.

[1025] 6. The server generates the final contract

[1026] The server generates a final version of the contract that reflects the amendments and provides it as a document such as a PDF file, which the user can download.

[1027] Drafting approval documents

[1028] 1. The user enters the approval information based on the contract information

[1029] The user reviews the final contract on the terminal and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval.

[1030] 2. The device sends the data to the server

[1031] The terminal transmits the input approval information to the server in data format.

[1032] 3. The server generates a draft request.

[1033] The server analyzes the received approval information, selects an appropriate approval template based on the AI ​​model, and automatically generates a draft approval document, which is then sent to the device.

[1034] 4. User checks and edits the draft

[1035] The user can review the draft approval document on their device and make any necessary corrections, such as changing the "budget details" or adding comments for the "risk assessment."

[1036] 5. The device sends the correction data to the server

[1037] The terminal transmits the user's modifications to the server again.

[1038] 6. The server generates the final approval document

[1039] The server generates a final version of the approval document that reflects the revisions and provides it as a document such as a PDF file, which the user can download.

[1040] Specific examples

[1041] Specific examples of contract creation

[1042] 1. The user enters the following: "Contract partner: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[1043] 2. The device sends this contract information to the server.

[1044] 3. The server generates a draft contract with the following information: "Contracting party: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[1045] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[1046] 5. The device sends the modifications to the server.

[1047] 6. The server finally generates the final contract with the following content: "Contract details: Sales of Product Y, Contract amount: 5 million yen, Contract expiration date: January 31, 2026" and provides it as a PDF file.

[1048] Specific examples of drafting approval documents

[1049] 1. The user enters approval information such as "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[1050] 2. The device sends this data to the server.

[1051] 3. The server generates a draft approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[1052] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[1053] 5. The device sends the modifications to the server.

[1054] 6. The server finally generates the final approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[1055] The above is a specific example of the operation of the embodiment of the present invention. This system improves the efficiency of the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[1056] The processing flow will be explained below.

[1057] Contract Creation Process

[1058] Step 1:

[1059] The user opens the contract creation page on their device and accesses the new contract creation form. The user enters the necessary information, such as the "contract date and time," "contract partner," "contract content," and "amount."

[1060] Step 2:

[1061] The terminal converts the entered contract information into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[1062] Step 3:

[1063] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information.

[1064] Step 4:

[1065] The server uses the AI ​​model to insert the contract information into the selected template and generate a draft contract, which is then converted back into a data format and sent to the device.

[1066] Step 5:

[1067] The user checks the draft contract displayed on the terminal and makes any necessary corrections, such as amending the contract amount or adding payment terms.

[1068] Step 6:

[1069] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[1070] Step 7:

[1071] The server generates the final contract based on the revised data, and saves the final contract as a PDF file or other document format.

[1072] Step 8:

[1073] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[1074] Approval document drafting process

[1075] Step 1:

[1076] The user checks the contract on their device and then moves to the page for creating a request for approval. The user enters information for the request, such as the purpose of the contract, the contracting party, the budget, and risk assessment, into the request for approval creation form.

[1077] Step 2:

[1078] The terminal converts the input approval information into a comprehensive data format (e.g., JSON) and sends it to the server, using the HTTPS protocol to ensure data security.

[1079] Step 3:

[1080] The server stores the received approval information in a database and uses it as input for the AI ​​model, which selects the most appropriate approval document template based on the approval information.

[1081] Step 4:

[1082] The server uses the AI ​​model to insert the approval request information into the selected template and generate a draft of the approval request document, which is then converted back into a data format and sent to the device.

[1083] Step 5:

[1084] The user checks the draft approval document displayed on the terminal and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments."

[1085] Step 6:

[1086] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[1087] Step 7:

[1088] The server generates a final approval document that reflects the corrections based on the corrected data, and saves the final approval document as a PDF file or other document format.

[1089] Step 8:

[1090] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[1091] Example 1

[1092] 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."

[1093] The traditional process for creating contracts and approval documents involves a lot of manual data entry, document generation, and editing, which results in low work efficiency and a high likelihood of problems due to input errors and inconsistent formats.In addition, it is difficult to standardize various documents, which can easily lead to variations in quality.

[1094] 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.

[1095] In this invention, the server includes input means for inputting contract data, transmission means for transmitting the input contract data to an information processing device, draft generation means for generating a contract draft based on the input contract data in the information processing device, transmission means for transmitting the generated contract draft to a terminal, correction means for the user to correct the contract draft, transmission means for transmitting the corrected contract draft to the information processing device, final contract generation means for generating a final contract reflecting the corrections, provision means for providing the generated final contract document, and means for using a generative AI model. This automates the process of creating contracts and approval documents, reducing input errors, improving work efficiency, and enabling the application of standardized formats.

[1096] "Input means" refers to a device or function that provides an interface for users to manually input contract data and approval data.

[1097] The "transmission means" is a communication device or function for transmitting data obtained by the input means to an information processing device or a server.

[1098] The "draft generation means" is a processing function or program for automatically generating a draft of a contract document or approval document based on the received data.

[1099] The "modification means" is a device or function that provides an interface for a user to check the generated draft of the contract document or approval document and modify the content as necessary.

[1100] The "final contract document generation means" is a processing function or program for generating a final contract document or approval document that reflects the corrections incorporated by the correction means.

[1101] The "means for providing" is a device or function for providing the generated final contract document or final approval document in a form that can be used by the user.

[1102] A "generative AI model" is an algorithm or system that uses machine learning techniques to select appropriate templates based on received data and automatically generate documents.

[1103] An "information processing device" is a computer or server that processes input data and provides various functions such as document generation.

[1104] A "terminal" is a device such as a personal computer, tablet, or smartphone that a user uses to enter contract information and approval information and to review and modify generated documents.

[1105] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments of this system will be described below.

[1106] Hardware and software used

[1107] Hardware: User devices (personal computers, tablets, smartphones, etc.), servers (high-performance computers)

[1108] Software: Web forms (front-end), server-side generative AI models (e.g., NLP-based template modelers)

[1109] System Overview

[1110] In this system, users input contract data and approval data using a terminal and send the information to a server, which then automatically generates draft contract and approval documents and provides the final documents. This streamlines the document creation process, reduces input errors, and enables the application of standardized formats.

[1111] Contract Creation Process

[1112] 1. The user enters the contract data using the terminal.

[1113] The user accesses the contract creation form using a web browser or a dedicated application, enters information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and clicks the "send" button.

[1114] 2. The device sends the data to the server

[1115] The terminal compiles the contract information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[1116] 3. The server generates a draft contract

[1117] The server parses the received JSON data and extracts the contract information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[1118] 4. User checks and edits the draft

[1119] The user can check the draft contract displayed on the terminal and modify it as necessary. For example, they can add information about the contracting party or modify the contract expiration date.

[1120] 5. The device sends the correction data to the server

[1121] The terminal sends the revised contract information again to the server in JSON format.

[1122] 6. The server generates the final contract

[1123] The server generates a final version of the contract that reflects the amendments, generates the final contract as a PDF document, and provides a link for the user to download it.

[1124] Approval document drafting process

[1125] 1. The user enters the approval request data based on the contract information

[1126] The user accesses the approval request creation form using a web browser or a dedicated application, reviews the final contract, and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment based on the contract's contents.

[1127] 2. The device sends the data to the server

[1128] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[1129] 3. The server generates a draft request.

[1130] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[1131] 4. User checks and edits the draft

[1132] The user can review the draft of the approval document displayed on the terminal and make corrections as necessary, for example, by changing the "budget details" or adding comments for the "risk assessment."

[1133] 5. The device sends the correction data to the server

[1134] The terminal sends the corrected approval information back to the server in JSON format.

[1135] 6. The server generates the final approval document

[1136] The server generates a final version of the approval document that reflects the changes, generates the final approval document as a PDF document, and provides a link for the user to download it.

[1137] Specific examples

[1138] Specific examples of contract creation

[1139] 1. The user enters the following information: "Contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[1140] 2. The device sends this contract information to the server.

[1141] 3. The server generates a draft contract with the following specifications: "Contracting party: a certain company, Contract content: product sales, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[1142] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[1143] 5. The device sends the modifications to the server.

[1144] 6. The server finally generates the final contract with the following content: "Contract details: product sales, contract amount: 5 million yen, contract expiration date: January 31, 2026" and provides it as a PDF file.

[1145] Specific examples of drafting approval documents

[1146] 1. The user enters the approval information, such as "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[1147] 2. The device sends this data to the server.

[1148] 3. The server generates a draft request form with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[1149] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[1150] 5. The device sends the modifications to the server.

[1151] 6. The server finally generates a final approval document with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[1152] As a result, the present invention streamlines the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[1153] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1154] Contract Creation Process

[1155] Step 1:

[1156] The user enters the contract data using the terminal.

[1157] The user accesses the contract creation form using a web browser or a dedicated application. They enter information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and then click the "Submit" button. The input data might include, for example, "contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[1158] Step 2:

[1159] The device sends data to the server

[1160] The terminal compiles the contract data entered by the user as JSON format data. The generated JSON data is sent to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format contract data, which is sent to the server.

[1161] Step 3:

[1162] The server generates a draft contract

[1163] The server parses the received JSON data and extracts the contract data. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract data to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated contract draft.

[1164] Step 4:

[1165] User reviews and edits the draft

[1166] The user checks the contract draft displayed on the terminal. If necessary, they modify the content, for example, adding "information about the contracting party" or modifying the "contract expiration date." The input data includes the content of the draft, especially the modified information. As a specific example of user behavior, the "contract expiration date" is modified to "January 31, 2026."

[1167] Step 5:

[1168] The device sends the correction data to the server

[1169] The terminal sends the modified contract data to the server again in JSON format. The input data contains the modified draft information, which is converted back to JSON format and provides the modified data that is sent to the server as output.

[1170] Step 6:

[1171] The server generates the final contract

[1172] The server generates a final contract that reflects the amendments. It generates the final contract as a PDF document and provides a link for the user to download it. The input data is the amended contract information, and the output is a PDF file of the final contract.

[1173] Approval document drafting process

[1174] Step 1:

[1175] The user enters approval data based on the contract information

[1176] The user accesses the approval request creation form using a web browser or a dedicated application. After reviewing the final contract, the user inputs information such as "contract purpose," "contract partner," "budget," and "risk assessment" based on the contract's contents. For example, input data might include "purpose: product sales, contract partner: certain company, budget: 5 million yen, risk: low."

[1177] Step 2:

[1178] The device sends data to the server

[1179] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format approval request data, which is sent to the server.

[1180] Step 3:

[1181] The server generates a draft request.

[1182] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated approval request draft.

[1183] Step 4:

[1184] User reviews and edits the draft

[1185] The user checks the draft approval document displayed on the terminal. If necessary, the user modifies the contents, for example, changing the "budget details" or adding a comment to the "risk assessment." The input data includes the contents of the draft, especially the modified information. As a specific example of user behavior, the user modifies the "budget" to "6 million yen."

[1186] Step 5:

[1187] The device sends the correction data to the server

[1188] The terminal sends the revised draft information to the server again in JSON format. The input data contains the revised draft information, which is converted back to JSON format and provides the revised data to be sent to the server as output.

[1189] Step 6:

[1190] The server generates the final approval document

[1191] The server generates a final version of the approval document that reflects the revisions. The final approval document is generated as a PDF document and a link is provided for users to download. The input data is the revised approval document information, and the output is a PDF file of the final approval document.

[1192] (Application example 1)

[1193] 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."

[1194] The process of creating contracts and approval documents has traditionally been done manually, resulting in time-consuming and labor-intensive processes, and the possibility of input errors and format inconsistencies. Furthermore, in situations where speedy transactions are required, such as electronic payment services, there is a growing demand for an automated system for generating contracts and approval documents that can respond smoothly and instantly. This project aims to solve these problems.

[1195] 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.

[1196] In this invention, the server includes an input means for inputting contract information, a transmission means for transmitting the input contract information to the server, a draft generation means for generating a contract draft based on the input contract information in the server, a transmission means for transmitting the generated contract draft to a terminal, a correction means for a user to correct the contract draft, a transmission means for transmitting the corrected contract draft to the server, a final contract generation means for generating a final contract reflecting the corrections, a provision means for providing the generated final contract, an automation means for inputting contract information and approval request information using a smartphone and automatically generating a contract and approval request using an AI model, and a download means for making the generated final contract and approval request request downloadable in PDF format. This significantly streamlines the process of creating contracts and approval requests, reduces input errors, enables the application of standardized formats, and enables rapid use of electronic payment services.

[1197] "Contract information" refers to information necessary to create a contract, and specifically includes information such as the contracting party, contract contents, contract amount, contract period, etc.

[1198] The "transmission means" is a means for sending information entered by the user to the server, and is a device or software that has the function of transferring data via a network.

[1199] A "draft generation means" is a device or software that has the function of automatically creating a draft of a contract or approval document based on input information.

[1200] A "terminal" is a device used by a user to input contract information and approval information and to review and revise drafts, and specifically includes smartphones, tablets, PCs, etc.

[1201] The "modification means" is a means by which the user can make necessary modifications to the generated draft, and is a device or software that allows the user to edit and change information.

[1202] The "final contract generation means" is a device or software that has the function of generating a final contract based on the revised draft.

[1203] The "means of provision" refers to the means for providing the generated final contract or request form to the user, and specifically includes providing a download link or sending it by email.

[1204] "Automation means" refers to a means for inputting contract information and approval request information using a smartphone and automatically generating contracts and approval requests using an AI model.

[1205] The "downloading means" is a means for allowing users to download the generated final contract or approval document in PDF format.

[1206] This invention is a system that automates the process of creating contracts and approval documents, and aims to generate documents efficiently and accurately by linking a smartphone with a server. To implement this invention, the following system configuration and software are used.

[1207] System Configuration

[1208] 1. Input method:

[1209] A user inputs contract information and approval information using a smartphone. The application on the smartphone provides a form for the user to input.

[1210] 2. Means of transmission:

[1211] The application installed on the smartphone sends the entered contract information and approval information to the server in JSON format.

[1212] 3. Draft generation method:

[1213] The server analyzes the received contract and approval information and generates optimal contract and approval drafts using an NLP (natural language processing)-based generative AI model that runs on a machine learning framework such as TensorFlow.

[1214] 4. Means of transmission:

[1215] The server then sends the generated draft to the smartphone in JSON format.

[1216] 5. Remedies:

[1217] Users can check the contract draft and approval draft on their smartphone and make any necessary revisions, which are then sent back to the server.

[1218] 6. Final contract generation means:

[1219] The server then generates the final contract and approval document, reflecting the changes. This process also utilizes the generative AI model.

[1220] 7. Means of provision:

[1221] The final contract and approval document will be made available for download by the user in PDF format.

[1222] Specific examples

[1223] As a concrete example, consider a case where a user enters the following information into a smartphone app: "Contract partner: a certain company, Contract details: product sales, Contract amount: 1 million yen, Contract expiration date: December 31, 2023." Once this information is entered, the app automatically sends the data to the server and generates a draft based on it. The user reviews the draft and corrects the "Contract amount" to "1.2 million yen," after which the final contract is generated and can be downloaded in PDF format.

[1224] Example of an input prompt for a generative AI model:

[1225] Based on the contract information entered by the user, the appropriate contract template is selected and a draft contract is generated that includes the following information:

[1226] 1. Contracting Party: A company

[1227] 2. Contents of the Agreement: Sale of Products

[1228] 3. Contract amount: 1 million yen

[1229] 4. Contract deadline: December 31, 2023

[1230] This invention will significantly streamline the process of creating contracts and approval documents, reducing input errors, applying standardized formats, and enabling faster electronic payment services.

[1231] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1232] Step 1:

[1233] The user uses a smartphone to input contract information and approval information. Specifically, they enter information such as the contracting party, contract content, contract amount, contract deadline, etc. into an input form. This input data is converted into JSON format.

[1234] Step 2:

[1235] The terminal sends the entered contract information and approval request information to the server. Specifically, it sends JSON format data to the server via an HTTP POST request. The input data is received on the server side.

[1236] Step 3:

[1237] The server analyzes the contract information and approval request information it receives and uses a generative AI model to generate a contract draft and approval request draft. Specifically, it uses an NLP (natural language processing)-based template modeler to select an appropriate template and automatically generate the draft. This generation process uses machine learning frameworks such as TensorFlow. The input is the contract information and approval request information, and the output is the generated draft.

[1238] Step 4:

[1239] The server sends the generated contract draft and approval document draft to the terminal. The draft is converted back to JSON format and sent to the terminal via HTTP POST or WebSocket communication. The data is received on the terminal side.

[1240] Step 5:

[1241] The user checks the contract draft and the approval request draft on their device and makes any necessary revisions. Specifically, they edit the wording and conditions in the draft and confirm the revisions. This revision data is also converted to JSON format.

[1242] Step 6:

[1243] The terminal sends the revised contract draft and approval draft to the server again. This data is sent to the server in JSON format via an HTTP POST request. The revised data is received on the server side.

[1244] Step 7:

[1245] The server reflects the revisions and generates the final contract and approval document. The generative AI model is then used again to automatically generate the final document reflecting the revisions. The input is the revised data, and the output is the final contract and approval document.

[1246] Step 8:

[1247] The server provides the final contract and approval document to the user through a delivery method. Specifically, the final document generated in PDF format is provided as a download link. It can also be sent by email if necessary. The input is the final document, and the output is a download link or email.

[1248] 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.

[1249] The present invention combines a system that automates the process of creating contracts and approval documents with an emotion engine that recognizes the user's emotions and adjusts the document content based on those emotions. Specific embodiments for implementing the program for this system are described below.

[1250] System Overview

[1251] This system allows users to input contract and approval information using a terminal, and then sends that information to a server, which then automatically generates drafts of the contract and approval documents and provides the final documents. Furthermore, the system has the ability to recognize the user's emotions using an emotion engine and adjust the document content accordingly.

[1252] Contract Creation Process

[1253] 1. The user enters the contract information using the terminal.

[1254] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount." At that time, the device's camera and microphone are used to analyze the user's facial expressions and voice, and emotional data is also collected.

[1255] 2. The device sends the data to the server

[1256] The terminal converts the entered contract information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[1257] 3. The server generates a draft contract

[1258] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information and emotion data.

[1259] 4. The server adjusts the draft based on the sentiment data.

[1260] The server adjusts the content of the generated contract draft based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it may emphasize important contract terms or insert additional explanations.

[1261] 5. User reviews and edits the draft

[1262] The user checks the draft contract displayed on the device and makes any necessary changes, such as amending the contract amount or adding payment terms. Emotional data is collected again during this process.

[1263] 6. The device sends the correction data and emotion data to the server.

[1264] The device transmits the user's corrections and the re-collected emotion data to the server.

[1265] 7. The server generates the final contract

[1266] The server generates a final contract based on the amendments and emotion data, and the final contract is saved and provided as a PDF file or other document format.

[1267] 8. Provision of the Final Agreement

[1268] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[1269] Approval document drafting process

[1270] 1. The user enters the approval information based on the contract information

[1271] The user reviews the final contract on the terminal, then enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval. Emotional data is also collected in the same way.

[1272] 2. The device sends the data to the server

[1273] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[1274] 3. The server generates a draft request.

[1275] The server stores the received approval information in a database and uses it as input for an AI model, which selects the most appropriate approval document template based on the approval information and emotion data.

[1276] 4. The server adjusts the draft based on the sentiment data.

[1277] The server adjusts the content of the generated draft request form based on the analysis results of the emotion engine. For example, if the user feels anxious, it adds a supplementary explanation to the risk assessment section.

[1278] 5. User reviews and edits the draft

[1279] The user checks the draft approval document displayed on the device and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotional data is collected again during this process.

[1280] 6. The device sends the correction data and emotion data to the server.

[1281] The device transmits the user's corrections and the re-collected emotion data to the server.

[1282] 7. The server generates the final approval document

[1283] The server generates a final approval document that reflects the corrections based on the correction data and emotion data. The generated final approval document is saved and provided as a PDF file or other document format.

[1284] 8. Providing the final approval document

[1285] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[1286] Specific examples

[1287] Specific examples of contract creation

[1288] 1. The user looks a little anxious as he enters the following information: "Contracting party: Company A, Contract details: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[1289] 2. The device sends the contract information and emotion data to the server.

[1290] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of Service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds, in emphasis, "Details of penalties regarding delivery delays" to reduce user anxiety.

[1291] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[1292] 5. The device sends the corrections and new emotion data to the server.

[1293] 6. The server finally generates the final contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[1294] Specific examples of drafting approval documents

[1295] 1. The user looks a little nervous as he enters the approval request information, such as "Purpose: provision of Service B, Contract partner: Company A, Budget: 2 million yen, Risk: Medium."

[1296] 2. The device sends these data and emotion data to the server.

[1297] 3. The server generates a draft approval document with the following specifications: "Objective: Provision of Service B, Contract Partner: Company A, Budget: 2 million yen, Risk: Medium" and adds a detailed analysis of the expected budget achievement to ease the user's tension.

[1298] 4. The user reviews the draft and corrects the "Budget" to "2.2 million yen."

[1299] 5. The device sends the corrections and new emotion data to the server.

[1300] 6. The server finally generates a final approval document with the following specifications: "Purpose: Provision of Service B, Contract Partner: Company A, Budget: 2.2 million yen, Risk: Medium" and provides it as a PDF file.

[1301] The above is a specific example of the operation of the embodiment of the present invention. This system makes it possible to create contracts and approval documents that take into account the user's emotions, thereby achieving more accurate and efficient business operations.

[1302] The processing flow will be explained below.

[1303] Contract Creation Process

[1304] Step 1:

[1305] The user opens the contract creation page on their device and accesses the new contract creation form. They enter the necessary information, such as the "contract date and time," "contract partner," "contract details," and "amount." While they are entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[1306] Step 2:

[1307] The terminal converts the entered contract information and emotional data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotional data includes emotions (e.g., joy, anxiety, surprise, etc.) analyzed from the user's facial expressions and voice.

[1308] Step 3:

[1309] The server stores the received contract information and emotion data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate contract template.

[1310] Step 4:

[1311] The server uses the AI ​​model to insert contract information into the selected template and generate a draft contract. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, it will emphasize or add additional explanations to specific parts of the contract (e.g., payment terms, delivery date).

[1312] Step 5:

[1313] The server sends a draft contract that has been adjusted based on the emotion data to the terminal. The user reviews the draft and makes any necessary changes, such as modifying the contract amount or adding payment terms. Emotion data continues to be collected even during the changes.

[1314] Step 6:

[1315] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[1316] Step 7:

[1317] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final contract, which is then saved as a document (e.g., PDF).

[1318] Step 8:

[1319] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[1320] Approval document drafting process

[1321] Step 1:

[1322] The user checks the contract on the device and then moves to a page for creating a request for approval. The user enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into the request for approval form. While the user is entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[1323] Step 2:

[1324] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotion data includes emotions (e.g., anger, anxiety, joy, etc.) analyzed from the user's facial expressions and voice.

[1325] Step 3:

[1326] The server stores the received approval information and sentiment data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate approval template.

[1327] Step 4:

[1328] The server uses the AI ​​model to insert the request information into the selected template and generate a draft request document. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, adds further explanations or supporting materials to the risk assessment section.

[1329] Step 5:

[1330] The server sends a draft of the approval document, adjusted based on the emotion data, to the terminal. The user reviews the draft and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotion data continues to be collected even during the corrections.

[1331] Step 6:

[1332] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[1333] Step 7:

[1334] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final approval document, which is then saved as a document (e.g., PDF).

[1335] Step 8:

[1336] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[1337] Example 2

[1338] 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."

[1339] The traditional process of creating contracts and approval documents involves a lot of manual input and correction, which is not only time-consuming and labor-intensive, but also makes it difficult to flexibly adjust the content of the document while taking into account the user's emotions.In addition, when users are in a situation where they feel anxious or stressed, they may not be able to properly understand the content of the document, which can result in incomplete contracts or approval documents.

[1340] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting contract information, a data collection means for collecting user emotion data, a transmission means for transmitting the input contract information and emotion data to the server, a draft generation means for generating a contract draft based on the input contract information in the server, an adjustment means for adjusting the contract draft generated based on the emotion data, a transmission means for transmitting the generated contract draft to the terminal, a correction means for the user to correct the contract draft, a transmission means for transmitting the corrected contract draft and the emotion data to the server, a final contract generation means for generating a final contract reflecting the corrections, and a provision means for providing the generated final contract. This enables the generation and adjustment of documents taking the user's emotions into consideration, thereby realizing a more accurate and efficient process for creating contracts and approval requests.

[1341] "Contract information" refers to information that the user inputs as necessary information for creating a contract, and specifically includes the date and time of the contract, the contracting party, the contract contents, the contract amount, and the like.

[1342] "Emotion data" is data that indicates the psychological state of the user, obtained by analyzing the user's facial expressions and voice, and refers to emotions such as anxiety, relief, and tension that the user expressed during the input task.

[1343] "Input means" refers to an interface for a user to input contract information into a terminal, and includes input devices such as a keyboard, a mouse, and a touch screen.

[1344] The "data collection means" refers to a means for collecting user emotional data, and includes a function for capturing the user's facial expressions and voice using the device's camera and microphone, and analyzing them using an emotion recognition engine.

[1345] "Transmission means" refers to the communication protocol for transmitting the entered contract information and emotion data to the server, and mainly includes secure communication means such as HTTPS.

[1346] "Draft generation means" refers to a means for automatically generating a draft of a contract based on contract information entered into the server, and uses a generation AI model.

[1347] "Adjustment means" refers to means for adjusting the content of the contract draft generated based on emotional data, and includes a function for optimizing the content and expression of the document according to the user's emotional state.

[1348] The "modification means" is an interface that allows the user to check the contract draft and modify it as necessary, and has the function of allowing text to be added or changed.

[1349] "Means for generating a final contract" refers to means for generating a final contract based on a revised draft contract, and includes a function for saving the final contract in a document format such as PDF.

[1350] "Means of provision" refers to the means for providing the generated final contract to the user, and includes methods such as generating a download link or notifying the user by email.

[1351] The present invention relates to a system for automating the process of creating contracts and approval documents and adjusting the content of the documents by analyzing user sentiment. The system includes the following components:

[1352] Hardware and Software Configuration

[1353] 1. Terminal

[1354] Input means: Provide an interface for users to input contract information using a keyboard, mouse, touch screen, etc.

[1355] Data collection method: The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice. The emotion recognition engine used is, for example, Microsoft Azure Emotion API.

[1356] Transmission method: The collected contract information and emotion data are converted into JSON format and sent to the server via the HTTPS protocol.

[1357] 2. Server

[1358] Draft generation means: The server stores the received contract information in a database (e.g., MySQL) and generates a contract draft using a generative AI model such as OpenAI's GPT-4.

[1359] Adjustment: The content of the generated draft contract is adjusted based on the sentiment data, such as emphasizing important points in the contract or adding additional explanations if the user feels uneasy.

[1360] Final contract generation method: Generate a final contract based on the revised draft contract. The final contract is saved in PDF format (e.g., by converting it to PDF format using the PyPDF2 library).

[1361] Provision method: A download link for the generated final contract is generated and provided to the user's device.

[1362] Specific examples

[1363] Specific examples of contract creation

[1364] 1. The user looks a little uneasy when entering the following information: "Contract partner: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[1365] 2. The device sends the contract information and emotion data to the server.

[1366] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds "Details of penalties regarding delivery delays" in an emphasised manner to reduce the user's concerns.

[1367] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[1368] 5. The device sends the corrections and new emotion data to the server.

[1369] 6. The server finally generates the final contract with the following details: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[1370] Specific examples of drafting approval documents

[1371] 1. The user looks a little nervous as he enters the approval request information, such as "Purpose: provision of Service B, Contract partner: Company A, Budget: 2 million yen, Risk: Medium."

[1372] 2. The device sends these data and emotion data to the server.

[1373] 3. The server generates a draft approval document with the following specifications: "Objective: Provision of Service B, Contracting Party: Company A, Budget: 2 million yen, Risk: Medium" and adds a detailed analysis of the expected budget achievement to ease the user's tension.

[1374] 4. The user reviews the draft and corrects the "Budget" to "2.2 million yen."

[1375] 5. The device sends the corrections and new emotion data to the server.

[1376] 6. The server finally generates a final approval document with the following criteria: "Purpose: Provision of Service B, Contracting Party: Company A, Budget: 2.2 million yen, Risk: Medium" and provides it as a PDF file.

[1377] Prompt Sentence Examples

[1378] Contract drafting prompt examples

[1379] "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[1380] Example prompts for creating approval documents

[1381] "Objective: Provision of Service B, Contractor: Company A, Budget: 2 million yen, Risk: Medium."

[1382] The above is an embodiment of the present invention. This system makes it possible to create contracts and approval documents that take the user's emotions into consideration, thereby achieving more accurate and efficient business operations.

[1383] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1384] Step 1:

[1385] The user inputs the contract information into the terminal. The user then inputs information such as "contract partner," "contract details," "contract amount," and "contract term" into the provided contract creation form. The input information is stored in the terminal as contract information data.

[1386] Step 2:

[1387] The device collects emotion data. The device uses a camera to capture the user's facial expressions and a microphone to collect voice data. This data is analyzed by an emotion recognition engine (e.g., Microsoft Azure Emotion API) and stored on the device as the user's emotion data.

[1388] Step 3:

[1389] The device sends the contract information and emotion data to the server. The device converts the contract information and emotion data into JSON format and sends it to the server using the HTTPS protocol. After the input data reaches the server, it is stored in a database.

[1390] Step 4:

[1391] The server generates a contract draft. Based on the received contract information, the server uses a generative AI model (e.g., GPT-4) to create a prompt sentence. The server inputs this prompt sentence into the AI ​​model, selects the most appropriate contract template, and generates a contract draft. The generated draft is saved on the server as draft data.

[1392] Step 5:

[1393] The server adjusts the contract draft based on the emotion data. The server adjusts the content of the draft data based on the analysis results of the emotion recognition engine. Specifically, if the user feels uneasy, the server emphasizes important points in the contract or inserts additional explanations. The adjusted draft is saved on the server as adjusted draft data.

[1394] Step 6:

[1395] The server sends the contract draft to the terminal, and the server sends the adjusted draft data to the terminal, and the terminal displays the received data and provides it to the user.

[1396] Step 7:

[1397] The user checks and amends the contract draft. The user checks the displayed contract draft and makes any necessary amendments. The amended data is saved on the terminal as amended draft data.

[1398] Step 8:

[1399] The device sends the revised draft data and emotion data to the server. The device converts the revised draft data and the re-collected emotion data into JSON format and sends it to the server using the HTTPS protocol. The sent data is stored on the server.

[1400] Step 9:

[1401] The server generates the final contract. The server generates the final contract based on the revised draft data and emotion data. The final contract is generated in PDF format (e.g., using the PyPDF2 library) and saved on the server as final contract data.

[1402] Step 10:

[1403] The server provides the final contract to the user. The server generates a download link for the final contract and sends it to the user's device. The user downloads the final contract through the device and saves it as needed.

[1404] The above process enables automatic generation and adjustment of contracts that take the user's feelings into consideration, realizing efficient and accurate contract creation.

[1405] (Application example 2)

[1406] 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."

[1407] In the process of creating contracts and approval documents, conventional methods require users to spend a lot of time entering and editing information, and do not take emotional states into consideration, resulting in problems of reduced efficiency and accuracy. Furthermore, in-store contract work requires particularly quick responses, which makes it necessary to reduce the emotional stress of users. To solve these issues, a system is needed that recognizes users' emotional data and automatically adjusts the content of contracts and approval documents based on that data.

[1408] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1409] In this invention, the server includes input means for inputting contract information, transmission means for transmitting the input contract information to the server, draft generation means for generating a contract draft on the server based on the input contract information, transmission means for transmitting the generated contract draft to the terminal, modification means for the user to modify the contract draft, transmission means for transmitting the modified contract draft to the server, final contract generation means for generating a final contract reflecting the modifications, provision means for providing the generated final contract, and emotion recognition means for recognizing user emotion data from a camera or microphone of the terminal and adjusting the content of the contract draft based on the emotion data. This makes it possible to efficiently and accurately create contracts and approval documents while taking the user's emotions into consideration.

[1410] The "input means" is a means for the user to input contract information into the terminal.

[1411] The "transmission means" is a means for the terminal to transmit the input contract information and the revised contract draft to the server.

[1412] The "draft generation means" is a means for the server to generate a contract draft based on the contract information input.

[1413] The "modification means" is a means by which the user can check the generated contract draft and modify it as necessary.

[1414] The "final contract generation means" is a means for generating a final contract based on the revised contract draft.

[1415] The "provision means" is a means for providing the generated final contract to the terminal.

[1416] The "emotion recognition means" is a means for recognizing the user's emotion data using the camera or microphone of the terminal and analyzing the data.

[1417] The present invention provides a system for improving the efficiency of the process of creating contracts and approval documents, and automatically generating documents that reflect the user's feelings. Specific embodiments for carrying out the present invention will be described below.

[1418] System Overview

[1419] This system allows users to input contract and approval information using a terminal, and then automatically generates drafts of the contract and approval documents by sending the information and emotional data to a server, which then provides the final documents after the user has confirmed and corrected them.The system uses the terminal's camera and microphone to recognize and analyze the emotional data.

[1420] Hardware and Software Configuration

[1421] The system includes the following hardware and software:

[1422] Terminal: Equipped with a camera and microphone for users to input contract information and collect emotional data.

[1423] Server: Generates drafts and final documents of contracts and approval documents.

[1424] Emotion Recognition Software: Software that analyzes a user's facial expressions and voice to obtain emotional data (e.g., "FaceAPI").

[1425] Machine learning models: Generative AI models (e.g., "GPT-4") for generating draft contracts and approval documents.

[1426] Data processing and calculation

[1427] 1. Enter and submit contract information:

[1428] The user enters contract information (e.g., contract date, contract partner, contract details, and amount) into a form on the device. The entered data, along with emotion data captured by the device's camera and microphone, is converted into JSON format and sent to the server using the HTTPS protocol.

[1429] 2. Draft generation and reflection of sentiment data:

[1430] The server stores the received contract information and emotion data in a database and uses them as input for a machine learning model. The generative AI model generates an optimal contract draft based on this data and adjusts the content using emotion recognition. For example, if the user is feeling anxious, the draft content is adjusted to emphasize important terms or additional explanations.

[1431] 3. Review and revise the draft:

[1432] The generated contract draft is sent to the terminal and confirmed by the user. The user then modifies the contract draft as necessary and sends the modifications and new emotion data back to the server.

[1433] 4. Generation and Delivery of Final Agreement:

[1434] The server generates the final contract based on the correction data and emotion data and provides it to the terminal. The final contract can then be downloaded in PDF format or other formats.

[1435] Specific examples

[1436] 1. Examples of contract drafting:

[1437] The user enters "Contract partner: Product Supply Co., Ltd., Contract content: Purchase of Product A, Contract amount: 500,000 yen, Contract expiration date: December 31, 2023."

[1438] Facial expression analysis determined that the user was slightly anxious.

[1439] The server generates a draft contract with the following terms: "Product Supply Co., Ltd., Procurement of Product A, Contract Amount: 500,000 yen, Contract Term: December 31, 2023," and emphasizes "detailed penalty conditions for delivery delays" to reduce anxiety.

[1440] The user checks the draft and corrects the "Contract Expiration Date" to "January 31, 2024."

[1441] The server finally creates a final contract stating "Product Supply Co., Ltd., Purchase of Product A, Contract Amount: 500,000 yen, Contract Expiry: January 31, 2024" and provides it as a PDF file.

[1442] 2. Example of drafting a request for approval:

[1443] The user enters "Purchase of Product A, Contract partner: Product Supply Co., Ltd., Budget: 500,000 yen, Risk: Medium."

[1444] Camera analysis determined that the user was in a tense state.

[1445] The server generates a draft approval document with the following specifications: "Objective: Procurement of Product A, Contractor: Product Supply Co., Ltd., Budget: 500,000 yen, Risk: Medium," and details the expected budget achievement to ease tension.

[1446] The user checks the draft and corrects the "Budget" to "550,000 yen."

[1447] The server finally creates a final approval document with the following description: "Purchase of Product A, Contractor: Product Supply Co., Ltd., Budget: 550,000 yen, Risk: Medium" and provides it as a PDF file.

[1448] Prompt Sentence Examples

[1449] Example prompts used to generate a draft contract:

[1450] Generate a draft agreement with the following contract information:

[1451] Counterparty: Product Supply Co., Ltd.

[1452] Contract details: Purchase of product A

[1453] Contract amount: 500,000 yen

[1454] User sentiment data supplement: The user appears anxious, so include additional explanations about important terms and conditions.

[1455] The above is an embodiment of the invention. This system makes it possible to create contracts and approval documents efficiently and accurately, taking into account the user's emotions.

[1456] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1457] Step 1:

[1458] Enter and send contract information and emotion data

[1459] The user uses a terminal to input contract information (contract date, contract partner, contract content, amount, etc.). The terminal collects this input data and also uses a camera and microphone to obtain the user's emotional data (facial expressions, tone of voice, etc.). This contract information and emotional data are converted into JSON format and sent to the server using the HTTPS protocol. The input is manual input by the user, and the output is JSON data sent to the server.

[1460] Step 2:

[1461] Emotion recognition and contract draft generation

[1462] The server stores the received contract information and emotional data in a database. It then analyzes the emotional data using emotion recognition software (e.g., FaceAPI) to determine the emotional state (e.g., anxiety, relief, tension). Based on the analysis results, the server uses a machine learning model (e.g., GPT-4) to generate an optimal contract draft. The server's input is JSON data, and its output is the initial contract draft.

[1463] Step 3:

[1464] Adjusting contract drafts using sentiment data

[1465] The server uses the analysis results of the emotion recognition software to adjust the content of the generated draft contract. If the user feels uneasy, it makes corrections such as highlighting important contract terms or inserting additional explanations into the draft contract. The input is the analysis results of the emotion recognition software and the draft contract, and the output is the adjusted draft contract.

[1466] Step 4:

[1467] Sending and reviewing a draft agreement

[1468] The terminal receives the adjusted contract draft and displays it to the user. The user checks the draft and makes any necessary corrections. After entering the corrections, the user sends the revised draft back to the server. The input is the corrections from the user, and the output is the revised contract draft.

[1469] Step 5:

[1470] Reflecting amendments and generating the final contract

[1471] The server receives the revised contract draft, reviews its contents again taking into account the emotional data, generates the final contract, and saves it in a format such as PDF. The input is the revised contract draft and the emotional data, and the output is the final contract.

[1472] Step 6:

[1473] Provision of final contract

[1474] The server generates a download link to provide the final contract to the terminal. The user downloads and saves the final contract through this link. The input is the final contract, and the output is the download link.

[1475] 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.

[1476] 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.

[1477] 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.

[1478] [Fourth embodiment]

[1479] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1480] 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.

[1481] 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).

[1482] 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.

[1483] 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.

[1484] 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).

[1485] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1486] 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.

[1487] 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.

[1488] 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.

[1489] 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.

[1490] 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.

[1491] 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."

[1492] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments for implementing the program of this system will be described below.

[1493] System Overview

[1494] In this system, users use a terminal to input contract information and approval information, and then send that information to a server, which then automatically generates a draft of the contract or approval document and provides the final document.

[1495] Contract Creation

[1496] 1. The user enters the contract information using the terminal.

[1497] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount," and then indicates completion of input.

[1498] 2. The device sends the data to the server

[1499] The terminal sends the entered contract information to the server in a data format (e.g., JSON).

[1500] 3. The server generates a draft contract

[1501] The server analyzes the received contract information, selects an appropriate contract template using an AI model (e.g., an NLP-based template modeler), and automatically generates a contract draft. The generated draft is then converted back into a data format and sent to the terminal.

[1502] 4. User checks and edits the draft

[1503] The user can check the draft contract on the terminal and make any necessary changes, such as modifying the "contracting party information" or adding "payment terms."

[1504] 5. The device sends the correction data to the server

[1505] The terminal transmits the user's modifications to the server again.

[1506] 6. The server generates the final contract

[1507] The server generates a final version of the contract that reflects the amendments and provides it as a document such as a PDF file, which the user can download.

[1508] Drafting approval documents

[1509] 1. The user enters the approval information based on the contract information

[1510] The user reviews the final contract on the terminal and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval.

[1511] 2. The device sends the data to the server

[1512] The terminal transmits the input approval information to the server in data format.

[1513] 3. The server generates a draft request.

[1514] The server analyzes the received approval information, selects an appropriate approval template based on the AI ​​model, and automatically generates a draft approval document, which is then sent to the device.

[1515] 4. User checks and edits the draft

[1516] The user can review the draft approval document on their device and make any necessary corrections, such as changing the "budget details" or adding comments for the "risk assessment."

[1517] 5. The device sends the correction data to the server

[1518] The terminal transmits the user's modifications to the server again.

[1519] 6. The server generates the final approval document

[1520] The server generates a final version of the approval document that reflects the revisions and provides it as a document such as a PDF file, which the user can download.

[1521] Specific examples

[1522] Specific examples of contract creation

[1523] 1. The user enters the following: "Contract partner: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[1524] 2. The device sends this contract information to the server.

[1525] 3. The server generates a draft contract with the following information: "Contracting party: Company X, Contract content: Sales of product Y, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[1526] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[1527] 5. The device sends the modifications to the server.

[1528] 6. The server finally generates the final contract with the following content: "Contract details: Sales of Product Y, Contract amount: 5 million yen, Contract expiration date: January 31, 2026" and provides it as a PDF file.

[1529] Specific examples of drafting approval documents

[1530] 1. The user enters approval information such as "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[1531] 2. The device sends this data to the server.

[1532] 3. The server generates a draft approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 5 million yen, Risk: Low."

[1533] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[1534] 5. The device sends the modifications to the server.

[1535] 6. The server finally generates the final approval document with the following specifications: "Objective: Sales of Product Y, Contract Partner: Company X, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[1536] The above is a specific example of the operation of the embodiment of the present invention. This system improves the efficiency of the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[1537] The processing flow will be explained below.

[1538] Contract Creation Process

[1539] Step 1:

[1540] The user opens the contract creation page on their device and accesses the new contract creation form. The user enters the necessary information, such as the "contract date and time," "contract partner," "contract content," and "amount."

[1541] Step 2:

[1542] The terminal converts the entered contract information into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[1543] Step 3:

[1544] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information.

[1545] Step 4:

[1546] The server uses the AI ​​model to insert the contract information into the selected template and generate a draft contract, which is then converted back into a data format and sent to the device.

[1547] Step 5:

[1548] The user checks the draft contract displayed on the terminal and makes any necessary corrections, such as amending the contract amount or adding payment terms.

[1549] Step 6:

[1550] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[1551] Step 7:

[1552] The server generates the final contract based on the revised data, and saves the final contract as a PDF file or other document format.

[1553] Step 8:

[1554] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[1555] Approval document drafting process

[1556] Step 1:

[1557] The user checks the contract on their device and then moves to the page for creating a request for approval. The user enters information for the request, such as the purpose of the contract, the contracting party, the budget, and risk assessment, into the request for approval creation form.

[1558] Step 2:

[1559] The terminal converts the input approval information into a comprehensive data format (e.g., JSON) and sends it to the server, using the HTTPS protocol to ensure data security.

[1560] Step 3:

[1561] The server stores the received approval information in a database and uses it as input for the AI ​​model, which selects the most appropriate approval document template based on the approval information.

[1562] Step 4:

[1563] The server uses the AI ​​model to insert the approval request information into the selected template and generate a draft of the approval request document, which is then converted back into a data format and sent to the device.

[1564] Step 5:

[1565] The user checks the draft approval document displayed on the terminal and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments."

[1566] Step 6:

[1567] The device converts the corrections into a data format and sends it back to the server, including the history of the corrections.

[1568] Step 7:

[1569] The server generates a final approval document that reflects the corrections based on the corrected data, and saves the final approval document as a PDF file or other document format.

[1570] Step 8:

[1571] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[1572] Example 1

[1573] 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."

[1574] The traditional process for creating contracts and approval documents involves a lot of manual data entry, document generation, and editing, which results in low work efficiency and a high likelihood of problems due to input errors and inconsistent formats.In addition, it is difficult to standardize various documents, which can easily lead to variations in quality.

[1575] 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.

[1576] In this invention, the server includes input means for inputting contract data, transmission means for transmitting the input contract data to an information processing device, draft generation means for generating a contract draft based on the input contract data in the information processing device, transmission means for transmitting the generated contract draft to a terminal, correction means for the user to correct the contract draft, transmission means for transmitting the corrected contract draft to the information processing device, final contract generation means for generating a final contract reflecting the corrections, provision means for providing the generated final contract document, and means for using a generative AI model. This automates the process of creating contracts and approval documents, reducing input errors, improving work efficiency, and enabling the application of standardized formats.

[1577] "Input means" refers to a device or function that provides an interface for users to manually input contract data and approval data.

[1578] The "transmission means" is a communication device or function for transmitting data obtained by the input means to an information processing device or a server.

[1579] The "draft generation means" is a processing function or program for automatically generating a draft of a contract document or approval document based on the received data.

[1580] The "modification means" is a device or function that provides an interface for a user to check the generated draft of the contract document or approval document and modify the content as necessary.

[1581] The "final contract document generation means" is a processing function or program for generating a final contract document or approval document that reflects the corrections incorporated by the correction means.

[1582] The "means for providing" is a device or function for providing the generated final contract document or final approval document in a form that can be used by the user.

[1583] A "generative AI model" is an algorithm or system that uses machine learning techniques to select appropriate templates based on received data and automatically generate documents.

[1584] An "information processing device" is a computer or server that processes input data and provides various functions such as document generation.

[1585] A "terminal" is a device such as a personal computer, tablet, or smartphone that a user uses to enter contract information and approval information and to review and modify generated documents.

[1586] The present invention is a system for automating the process of creating contracts and approval documents. Specific embodiments of this system will be described below.

[1587] Hardware and software used

[1588] Hardware: User devices (personal computers, tablets, smartphones, etc.), servers (high-performance computers)

[1589] Software: Web forms (front-end), server-side generative AI models (e.g., NLP-based template modelers)

[1590] System Overview

[1591] In this system, users input contract data and approval data using a terminal and send the information to a server, which then automatically generates draft contract and approval documents and provides the final documents. This streamlines the document creation process, reduces input errors, and enables the application of standardized formats.

[1592] Contract Creation Process

[1593] 1. The user enters the contract data using the terminal.

[1594] The user accesses the contract creation form using a web browser or a dedicated application, enters information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and clicks the "send" button.

[1595] 2. The device sends the data to the server

[1596] The terminal compiles the contract information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[1597] 3. The server generates a draft contract

[1598] The server parses the received JSON data and extracts the contract information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[1599] 4. User checks and edits the draft

[1600] The user can check the draft contract displayed on the terminal and modify it as necessary. For example, they can add information about the contracting party or modify the contract expiration date.

[1601] 5. The device sends the correction data to the server

[1602] The terminal sends the revised contract information again to the server in JSON format.

[1603] 6. The server generates the final contract

[1604] The server generates a final version of the contract that reflects the amendments, generates the final contract as a PDF document, and provides a link for the user to download it.

[1605] Approval document drafting process

[1606] 1. The user enters the approval request data based on the contract information

[1607] The user accesses the approval request creation form using a web browser or a dedicated application, reviews the final contract, and enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment based on the contract's contents.

[1608] 2. The device sends the data to the server

[1609] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request.

[1610] 3. The server generates a draft request.

[1611] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, and returns this draft in JSON format to the terminal.

[1612] 4. User checks and edits the draft

[1613] The user can review the draft of the approval document displayed on the terminal and make corrections as necessary, for example, by changing the "budget details" or adding comments for the "risk assessment."

[1614] 5. The device sends the correction data to the server

[1615] The terminal sends the corrected approval information back to the server in JSON format.

[1616] 6. The server generates the final approval document

[1617] The server generates a final version of the approval document that reflects the changes, generates the final approval document as a PDF document, and provides a link for the user to download it.

[1618] Specific examples

[1619] Specific examples of contract creation

[1620] 1. The user enters the following information: "Contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[1621] 2. The device sends this contract information to the server.

[1622] 3. The server generates a draft contract with the following specifications: "Contracting party: a certain company, Contract content: product sales, Contract amount: 5 million yen, Contract expiration date: December 31, 2025."

[1623] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2026."

[1624] 5. The device sends the modifications to the server.

[1625] 6. The server finally generates the final contract with the following content: "Contract details: product sales, contract amount: 5 million yen, contract expiration date: January 31, 2026" and provides it as a PDF file.

[1626] Specific examples of drafting approval documents

[1627] 1. The user enters the approval information, such as "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[1628] 2. The device sends this data to the server.

[1629] 3. The server generates a draft request form with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 5 million yen, Risk: Low."

[1630] 4. The user reviews the draft and corrects the "Budget" to "6 million yen."

[1631] 5. The device sends the modifications to the server.

[1632] 6. The server finally generates a final approval document with the following specifications: "Purpose: Product sales, Contract partner: Certain company, Budget: 6 million yen, Risk: Low" and provides it as a PDF file.

[1633] As a result, the present invention streamlines the process of creating contracts and approval documents, reduces input errors, and makes it easier to apply standardized formats.

[1634] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1635] Contract Creation Process

[1636] Step 1:

[1637] The user enters the contract data using the terminal.

[1638] The user accesses the contract creation form using a web browser or a dedicated application. They enter information such as the "contract date and time," "contract partner," "contract content," and "amount" into the form displayed on the screen, and then click the "Submit" button. The input data might include, for example, "contract partner: a certain company, contract content: product sales, contract amount: 5 million yen, contract expiration date: December 31, 2025."

[1639] Step 2:

[1640] The device sends data to the server

[1641] The terminal compiles the contract data entered by the user as JSON format data. The generated JSON data is sent to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format contract data, which is sent to the server.

[1642] Step 3:

[1643] The server generates a draft contract

[1644] The server parses the received JSON data and extracts the contract data. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate contract template. It applies the contract data to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated contract draft.

[1645] Step 4:

[1646] User reviews and edits the draft

[1647] The user checks the contract draft displayed on the terminal. If necessary, they modify the content, for example, adding "information about the contracting party" or modifying the "contract expiration date." The input data includes the content of the draft, especially the modified information. As a specific example of user behavior, the "contract expiration date" is modified to "January 31, 2026."

[1648] Step 5:

[1649] The device sends the correction data to the server

[1650] The terminal sends the modified contract data to the server again in JSON format. The input data contains the modified draft information, which is converted back to JSON format and provides the modified data that is sent to the server as output.

[1651] Step 6:

[1652] The server generates the final contract

[1653] The server generates a final contract that reflects the amendments. It generates the final contract as a PDF document and provides a link for the user to download it. The input data is the amended contract information, and the output is a PDF file of the final contract.

[1654] Approval document drafting process

[1655] Step 1:

[1656] The user enters approval data based on the contract information

[1657] The user accesses the approval request creation form using a web browser or a dedicated application. After reviewing the final contract, the user inputs information such as "contract purpose," "contract partner," "budget," and "risk assessment" based on the contract's contents. For example, input data might include "purpose: product sales, contract partner: certain company, budget: 5 million yen, risk: low."

[1658] Step 2:

[1659] The device sends data to the server

[1660] The terminal compiles the approval request information entered by the user as JSON format data and sends it to the server using an HTTP POST request. Data processing based on the input data refers to converting form data into JSON format data. The output is JSON format approval request data, which is sent to the server.

[1661] Step 3:

[1662] The server generates a draft request.

[1663] The server parses the received JSON data and extracts the approval request information. Based on the extracted information, it uses an NLP-based template modeler (generative AI model) to select an appropriate approval request template. It applies the approval request information to the template to generate a draft, which is then returned to the terminal in JSON format. The input is the received JSON data, and the output is the JSON data of the generated approval request draft.

[1664] Step 4:

[1665] User reviews and edits the draft

[1666] The user checks the draft approval document displayed on the terminal. If necessary, the user modifies the contents, for example, changing the "budget details" or adding a comment to the "risk assessment." The input data includes the contents of the draft, especially the modified information. As a specific example of user behavior, the user modifies the "budget" to "6 million yen."

[1667] Step 5:

[1668] The device sends the correction data to the server

[1669] The terminal sends the revised draft information to the server again in JSON format. The input data contains the revised draft information, which is converted back to JSON format and provides the revised data to be sent to the server as output.

[1670] Step 6:

[1671] The server generates the final approval document

[1672] The server generates a final version of the approval document that reflects the revisions. The final approval document is generated as a PDF document and a link is provided for users to download. The input data is the revised approval document information, and the output is a PDF file of the final approval document.

[1673] (Application example 1)

[1674] 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."

[1675] The process of creating contracts and approval documents has traditionally been done manually, resulting in time-consuming and labor-intensive processes, and the possibility of input errors and format inconsistencies. Furthermore, in situations where speedy transactions are required, such as electronic payment services, there is a growing demand for an automated system for generating contracts and approval documents that can respond smoothly and instantly. This project aims to solve these problems.

[1676] 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.

[1677] In this invention, the server includes an input means for inputting contract information, a transmission means for transmitting the input contract information to the server, a draft generation means for generating a contract draft based on the input contract information in the server, a transmission means for transmitting the generated contract draft to a terminal, a correction means for a user to correct the contract draft, a transmission means for transmitting the corrected contract draft to the server, a final contract generation means for generating a final contract reflecting the corrections, a provision means for providing the generated final contract, an automation means for inputting contract information and approval request information using a smartphone and automatically generating a contract and approval request using an AI model, and a download means for making the generated final contract and approval request request downloadable in PDF format. This significantly streamlines the process of creating contracts and approval requests, reduces input errors, enables the application of standardized formats, and enables rapid use of electronic payment services.

[1678] "Contract information" refers to information necessary to create a contract, and specifically includes information such as the contracting party, contract contents, contract amount, contract period, etc.

[1679] The "transmission means" is a means for sending information entered by the user to the server, and is a device or software that has the function of transferring data via a network.

[1680] A "draft generation means" is a device or software that has the function of automatically creating a draft of a contract or approval document based on input information.

[1681] A "terminal" is a device used by a user to input contract information and approval information and to review and revise drafts, and specifically includes smartphones, tablets, PCs, etc.

[1682] The "modification means" is a means by which the user can make necessary modifications to the generated draft, and is a device or software that allows the user to edit and change information.

[1683] The "final contract generation means" is a device or software that has the function of generating a final contract based on the revised draft.

[1684] The "means of provision" refers to the means for providing the generated final contract or request form to the user, and specifically includes providing a download link or sending it by email.

[1685] "Automation means" refers to a means for inputting contract information and approval request information using a smartphone and automatically generating contracts and approval requests using an AI model.

[1686] The "downloading means" is a means for allowing users to download the generated final contract or approval document in PDF format.

[1687] This invention is a system that automates the process of creating contracts and approval documents, and aims to generate documents efficiently and accurately by linking a smartphone with a server. To implement this invention, the following system configuration and software are used.

[1688] System Configuration

[1689] 1. Input method:

[1690] A user inputs contract information and approval information using a smartphone. The application on the smartphone provides a form for the user to input.

[1691] 2. Means of transmission:

[1692] The application installed on the smartphone sends the entered contract information and approval information to the server in JSON format.

[1693] 3. Draft generation method:

[1694] The server analyzes the received contract and approval information and generates optimal contract and approval drafts using an NLP (natural language processing)-based generative AI model that runs on a machine learning framework such as TensorFlow.

[1695] 4. Means of transmission:

[1696] The server then sends the generated draft to the smartphone in JSON format.

[1697] 5. Remedies:

[1698] Users can check the contract draft and approval draft on their smartphone and make any necessary revisions, which are then sent back to the server.

[1699] 6. Final contract generation means:

[1700] The server then generates the final contract and approval document, reflecting the changes. This process also utilizes the generative AI model.

[1701] 7. Means of provision:

[1702] The final contract and approval document will be made available for download by the user in PDF format.

[1703] Specific examples

[1704] As a concrete example, consider a case where a user enters the following information into a smartphone app: "Contract partner: a certain company, Contract details: product sales, Contract amount: 1 million yen, Contract expiration date: December 31, 2023." Once this information is entered, the app automatically sends the data to the server and generates a draft based on it. The user reviews the draft and corrects the "Contract amount" to "1.2 million yen," after which the final contract is generated and can be downloaded in PDF format.

[1705] Example of an input prompt for a generative AI model:

[1706] Based on the contract information entered by the user, the appropriate contract template is selected and a draft contract is generated that includes the following information:

[1707] 1. Contracting Party: A company

[1708] 2. Contents of the Agreement: Sale of Products

[1709] 3. Contract amount: 1 million yen

[1710] 4. Contract deadline: December 31, 2023

[1711] This invention will significantly streamline the process of creating contracts and approval documents, reducing input errors, applying standardized formats, and enabling faster electronic payment services.

[1712] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1713] Step 1:

[1714] The user uses a smartphone to input contract information and approval information. Specifically, they enter information such as the contracting party, contract content, contract amount, contract deadline, etc. into an input form. This input data is converted into JSON format.

[1715] Step 2:

[1716] The terminal sends the entered contract information and approval request information to the server. Specifically, it sends JSON format data to the server via an HTTP POST request. The input data is received on the server side.

[1717] Step 3:

[1718] The server analyzes the contract information and approval request information it receives and uses a generative AI model to generate a contract draft and approval request draft. Specifically, it uses an NLP (natural language processing)-based template modeler to select an appropriate template and automatically generate the draft. This generation process uses machine learning frameworks such as TensorFlow. The input is the contract information and approval request information, and the output is the generated draft.

[1719] Step 4:

[1720] The server sends the generated contract draft and approval document draft to the terminal. The draft is converted back to JSON format and sent to the terminal via HTTP POST or WebSocket communication. The data is received on the terminal side.

[1721] Step 5:

[1722] The user checks the contract draft and the approval request draft on their device and makes any necessary revisions. Specifically, they edit the wording and conditions in the draft and confirm the revisions. This revision data is also converted to JSON format.

[1723] Step 6:

[1724] The terminal sends the revised contract draft and approval draft to the server again. This data is sent to the server in JSON format via an HTTP POST request. The revised data is received on the server side.

[1725] Step 7:

[1726] The server reflects the revisions and generates the final contract and approval document. The generative AI model is then used again to automatically generate the final document reflecting the revisions. The input is the revised data, and the output is the final contract and approval document.

[1727] Step 8:

[1728] The server provides the final contract and approval document to the user through a delivery method. Specifically, the final document generated in PDF format is provided as a download link. It can also be sent by email if necessary. The input is the final document, and the output is a download link or email.

[1729] 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.

[1730] The present invention combines a system that automates the process of creating contracts and approval documents with an emotion engine that recognizes the user's emotions and adjusts the document content based on those emotions. Specific embodiments for implementing the program for this system are described below.

[1731] System Overview

[1732] This system allows users to input contract and approval information using a terminal, and then sends that information to a server, which then automatically generates drafts of the contract and approval documents and provides the final documents. Furthermore, the system has the ability to recognize the user's emotions using an emotion engine and adjust the document content accordingly.

[1733] Contract Creation Process

[1734] 1. The user enters the contract information using the terminal.

[1735] From the terminal where the user has logged in, the user enters the necessary information into the contract creation form, such as the "contract date and time," "contract partner," "contract content," and "amount." At that time, the device's camera and microphone are used to analyze the user's facial expressions and voice, and emotional data is also collected.

[1736] 2. The device sends the data to the server

[1737] The terminal converts the entered contract information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[1738] 3. The server generates a draft contract

[1739] The server stores the received contract information in a database and uses it as input for an AI model, which selects the most appropriate contract template based on the contract information and emotion data.

[1740] 4. The server adjusts the draft based on the sentiment data.

[1741] The server adjusts the content of the generated contract draft based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it may emphasize important contract terms or insert additional explanations.

[1742] 5. User reviews and edits the draft

[1743] The user checks the draft contract displayed on the device and makes any necessary changes, such as amending the contract amount or adding payment terms. Emotional data is collected again during this process.

[1744] 6. The device sends the correction data and emotion data to the server.

[1745] The device transmits the user's corrections and the re-collected emotion data to the server.

[1746] 7. The server generates the final contract

[1747] The server generates a final contract based on the amendments and emotion data, and the final contract is saved and provided as a PDF file or other document format.

[1748] 8. Provision of the Final Agreement

[1749] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[1750] Approval document drafting process

[1751] 1. The user enters the approval information based on the contract information

[1752] The user reviews the final contract on the terminal, then enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into a form for creating a request for approval. Emotional data is also collected in the same way.

[1753] 2. The device sends the data to the server

[1754] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server using the HTTPS protocol to ensure data security.

[1755] 3. The server generates a draft request.

[1756] The server stores the received approval information in a database and uses it as input for an AI model, which selects the most appropriate approval document template based on the approval information and emotion data.

[1757] 4. The server adjusts the draft based on the sentiment data.

[1758] The server adjusts the content of the generated draft request form based on the analysis results of the emotion engine. For example, if the user feels anxious, it adds a supplementary explanation to the risk assessment section.

[1759] 5. User reviews and edits the draft

[1760] The user checks the draft approval document displayed on the device and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotional data is collected again during this process.

[1761] 6. The device sends the correction data and emotion data to the server.

[1762] The device transmits the user's corrections and the re-collected emotion data to the server.

[1763] 7. The server generates the final approval document

[1764] The server generates a final approval document that reflects the corrections based on the correction data and emotion data. The generated final approval document is saved and provided as a PDF file or other document format.

[1765] 8. Providing the final approval document

[1766] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[1767] Specific examples

[1768] Specific examples of contract creation

[1769] 1. The user looks a little anxious as he enters the following information: "Contracting party: Company A, Contract details: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[1770] 2. The device sends the contract information and emotion data to the server.

[1771] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of Service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds, in emphasis, "Details of penalties regarding delivery delays" to reduce user anxiety.

[1772] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[1773] 5. The device sends the corrections and new emotion data to the server.

[1774] 6. The server finally generates the final contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[1775] Specific examples of drafting approval documents

[1776] 1. The user looks a little nervous as he enters the approval request information, such as "Purpose: provision of Service B, Contract partner: Company A, Budget: 2 million yen, Risk: Medium."

[1777] 2. The device sends these data and emotion data to the server.

[1778] 3. The server generates a draft approval document with the following specifications: "Objective: Provision of Service B, Contract Partner: Company A, Budget: 2 million yen, Risk: Medium" and adds a detailed analysis of the expected budget achievement to ease the user's tension.

[1779] 4. The user reviews the draft and corrects the "Budget" to "2.2 million yen."

[1780] 5. The device sends the corrections and new emotion data to the server.

[1781] 6. The server finally generates a final approval document with the following specifications: "Purpose: Provision of Service B, Contract Partner: Company A, Budget: 2.2 million yen, Risk: Medium" and provides it as a PDF file.

[1782] The above is a specific example of the operation of the embodiment of the present invention. This system makes it possible to create contracts and approval documents that take into account the user's emotions, thereby achieving more accurate and efficient business operations.

[1783] The processing flow will be explained below.

[1784] Contract Creation Process

[1785] Step 1:

[1786] The user opens the contract creation page on their device and accesses the new contract creation form. They enter the necessary information, such as the "contract date and time," "contract partner," "contract details," and "amount." While they are entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[1787] Step 2:

[1788] The terminal converts the entered contract information and emotional data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotional data includes emotions (e.g., joy, anxiety, surprise, etc.) analyzed from the user's facial expressions and voice.

[1789] Step 3:

[1790] The server stores the received contract information and emotion data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate contract template.

[1791] Step 4:

[1792] The server uses the AI ​​model to insert contract information into the selected template and generate a draft contract. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, it will emphasize or add additional explanations to specific parts of the contract (e.g., payment terms, delivery date).

[1793] Step 5:

[1794] The server sends a draft contract that has been adjusted based on the emotion data to the terminal. The user reviews the draft and makes any necessary changes, such as modifying the contract amount or adding payment terms. Emotion data continues to be collected even during the changes.

[1795] Step 6:

[1796] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[1797] Step 7:

[1798] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final contract, which is then saved as a document (e.g., PDF).

[1799] Step 8:

[1800] The server generates a download link for providing the final contract to the terminal and provides it to the user, who then downloads and saves the final contract through the terminal.

[1801] Approval document drafting process

[1802] Step 1:

[1803] The user checks the contract on the device and then moves to a page for creating a request for approval. The user enters information such as the purpose of the contract, the contracting party, the budget, and risk assessment into the request for approval form. While the user is entering information, the device's camera and microphone capture the user's facial expressions and voice, collecting emotional data.

[1804] Step 2:

[1805] The device converts the input approval information and emotion data into a comprehensive data format (e.g., JSON) and sends it to the server. The emotion data includes emotions (e.g., anger, anxiety, joy, etc.) analyzed from the user's facial expressions and voice.

[1806] Step 3:

[1807] The server stores the received approval information and emotion data in a database, and then inputs this data into an AI model (e.g., an NLP-based template engine) to select the most appropriate approval template.

[1808] Step 4:

[1809] The server uses the AI ​​model to insert the request information into the selected template and generate a draft request document. The emotion engine then analyzes the user's emotional data and, if it detects emotions such as anxiety or tension, adds further explanations or supporting materials to the risk assessment section.

[1810] Step 5:

[1811] The server sends a draft of the approval document, adjusted based on the emotion data, to the terminal. The user reviews the draft and makes any necessary corrections, such as "revising the budget" or "adding risk assessment comments." Emotion data continues to be collected even during the corrections.

[1812] Step 6:

[1813] The device then sends the user's edits and the newly collected emotion data back to the server, including the edit history and the latest emotion data.

[1814] Step 7:

[1815] The server analyzes the sentiment data again and adds any necessary explanations or emphasis before generating the final approval document, which is then saved as a document (e.g., PDF).

[1816] Step 8:

[1817] The server generates a download link for providing the final approval document to the terminal and provides it to the user. The user downloads and saves the final approval document through the terminal.

[1818] Example 2

[1819] 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."

[1820] The traditional process of creating contracts and approval documents involves a lot of manual input and correction, which is not only time-consuming and labor-intensive, but also makes it difficult to flexibly adjust the content of the document while taking into account the user's emotions.In addition, when users are in a situation where they feel anxious or stressed, they may not be able to properly understand the content of the document, which can result in incomplete contracts or approval documents.

[1821] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting contract information, a data collection means for collecting user emotion data, a transmission means for transmitting the input contract information and emotion data to the server, a draft generation means for generating a contract draft based on the input contract information in the server, an adjustment means for adjusting the contract draft generated based on the emotion data, a transmission means for transmitting the generated contract draft to the terminal, a correction means for the user to correct the contract draft, a transmission means for transmitting the corrected contract draft and the emotion data to the server, a final contract generation means for generating a final contract reflecting the corrections, and a provision means for providing the generated final contract. This enables the generation and adjustment of documents taking the user's emotions into consideration, thereby realizing a more accurate and efficient process for creating contracts and approval requests.

[1822] "Contract information" refers to information that the user inputs as necessary information for creating a contract, and specifically includes the date and time of the contract, the contracting party, the contract contents, the contract amount, and the like.

[1823] "Emotion data" is data that indicates the psychological state of the user, obtained by analyzing the user's facial expressions and voice, and refers to emotions such as anxiety, relief, and tension that the user expressed during the input task.

[1824] "Input means" refers to an interface for a user to input contract information into a terminal, and includes input devices such as a keyboard, a mouse, and a touch screen.

[1825] The "data collection means" refers to a means for collecting user emotional data, and includes a function for capturing the user's facial expressions and voice using the device's camera and microphone, and analyzing them using an emotion recognition engine.

[1826] "Transmission means" refers to the communication protocol for transmitting the entered contract information and emotion data to the server, and mainly includes secure communication means such as HTTPS.

[1827] "Draft generation means" refers to a means for automatically generating a draft of a contract based on contract information entered into the server, and uses a generation AI model.

[1828] "Adjustment means" refers to means for adjusting the content of the contract draft generated based on emotional data, and includes a function for optimizing the content and expression of the document according to the user's emotional state.

[1829] The "modification means" is an interface that allows the user to check the contract draft and modify it as necessary, and has the function of allowing text to be added or changed.

[1830] "Means for generating a final contract" refers to means for generating a final contract based on a revised draft contract, and includes a function for saving the final contract in a document format such as PDF.

[1831] "Means of provision" refers to the means for providing the generated final contract to the user, and includes methods such as generating a download link or notifying the user by email.

[1832] The present invention relates to a system for automating the process of creating contracts and approval documents and adjusting the content of the documents by analyzing user sentiment. The system includes the following components:

[1833] Hardware and Software Configuration

[1834] 1. Terminal

[1835] Input means: Provide an interface for users to input contract information using a keyboard, mouse, touch screen, etc.

[1836] Data collection method: The device is equipped with a camera and microphone, which are used to capture the user's facial expressions and voice. The emotion recognition engine used is, for example, Microsoft Azure Emotion API.

[1837] Transmission method: The collected contract information and emotion data are converted into JSON format and sent to the server via the HTTPS protocol.

[1838] 2. Server

[1839] Draft generation means: The server stores the received contract information in a database (e.g., MySQL) and generates a contract draft using a generative AI model such as OpenAI's GPT-4.

[1840] Adjustment: The content of the generated draft contract is adjusted based on the sentiment data, such as emphasizing important points in the contract or adding additional explanations if the user feels uneasy.

[1841] Final contract generation method: Generate a final contract based on the revised draft contract. The final contract is saved in PDF format (e.g., by converting it to PDF format using the PyPDF2 library).

[1842] Provision method: A download link for the generated final contract is generated and provided to the user's device.

[1843] Specific examples

[1844] Specific examples of contract creation

[1845] 1. The user looks a little uneasy when entering the following information: "Contract partner: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023."

[1846] 2. The device sends the contract information and emotion data to the server.

[1847] 3. The server generates a draft contract with the following information: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: December 31, 2023," and adds "Details of penalties regarding delivery delays" in an emphasised manner to reduce the user's concerns.

[1848] 4. The user reviews the draft and modifies the "Contract Expiration Date" to "January 31, 2024."

[1849] 5. The device sends the corrections and new emotion data to the server.

[1850] 6. The server finally generates the final contract with the following details: "Contracting party: Company A, Contract content: Provision of service B, Contract amount: 2 million yen, Contract expiration date: January 31, 2024" and provides it as a PDF file.

[1851] Specific examples of drafting approval documents

[1852] 1. The user looks a little nervous as he enter...

Claims

1. an input means for inputting contract information; a transmission means for transmitting the input contract information to a server; a draft generation means for generating a contract draft based on contract information input in the server; a transmission means for transmitting the generated contract draft to a terminal; A means for a user to amend the contract draft; a sending means for sending the amended draft contract to the server; a final contract generation means for generating a final contract that reflects the amendments; a means for providing the generated final contract; A system including:

2. A draft of the approval document is generated based on the input approval information, After the user has revised the draft request, the final request is generated and provided. The system of claim 1 .

3. In generating the contract draft and the approval document draft, Use machine learning models The system of claim 1 .

Images