System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving content entered by a user in natural language; means for analyzing the received natural language content to extract requirements of a contract; means for generating a draft of the contract based on the extracted requirements; means for displaying the generated draft to the user; means for receiving revised content from the user and generating a final contract draft; and means for storing the final contract draft.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional contract creation methods require legal knowledge, making it difficult for ordinary users to create contracts efficiently and accurately. This requires the involvement of experts, which increases the time and cost involved. Another issue is the complicated process of accurately converting contract content expressed in natural language into contract format. [Means for solving the problem]

[0005] The present invention provides a system that receives content entered by a user in natural language, analyzes that content, extracts contract requirements, and automatically generates a draft contract. It also has the ability to receive content revised by the user again, generate a final contract draft, and save it. This system allows even users without legal knowledge to create contracts efficiently and accurately. The use of a natural language processing engine makes it possible to accurately analyze contract content expressed in natural language, and generate appropriate contracts that include legal clauses.

[0006] "User" means any person or entity that uses the System.

[0007] A "natural language" is a language that people use on a daily basis, and is different from artificial languages ​​such as programming languages.

[0008] "Input" refers to the act of a user providing information or data to a system.

[0009] "Receiving" is the process by which a system takes input from a user.

[0010] "Analysis" is the process by which a system understands the information it receives and extracts the necessary elements.

[0011] "Requirements" refer to the items and conditions necessary for generating a contract.

[0012] "Extraction" refers to the act of extracting important information obtained through analysis.

[0013] "Draft" means a draft of the Agreement, an incomplete document before the User has reviewed or revised it.

[0014] "Display" refers to the act of presenting the system-generated draft to the user in a visible form.

[0015] "Modification" refers to the act of a user making changes or additions to a generated draft.

[0016] "Storage" refers to the act of having the system store the final contract draft so that it can be retrieved as needed.

[0017] "System" means a collection of devices and programs that includes a set of processes that receive and analyze user input and generate, display, and store draft contracts.

[0018] A "natural language processing engine" is software that analyzes information expressed in natural language and converts it into structured data.

[0019] "Legal Terms" are the legally significant terms and conditions that must be included in a contract. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. An embodiment of the present invention includes a process in which a user enters contract content in natural language via a terminal, and the input content is analyzed by a server and generated as a draft contract.

[0042] A natural language description of what the program does

[0043] 1. User Input

[0044] The user enters the contract details in natural language into the input field on the terminal. For example, they enter something like "Company A will supply products to Company B every month, and Company B will pay for them."

[0045] 2. Receiving input

[0046] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using a secure communication protocol such as HTTPS.

[0047] 3. Natural Language Analysis

[0048] The server passes the received contract content in natural language to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, products, payment terms).

[0049] 4. Generate a draft

[0050] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and generates a draft contract by embedding the extracted requirements into the template. For example, a draft contract may be generated stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0051] 5. Viewing Drafts

[0052] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[0053] 6. Receiving and Regenerating Modifications

[0054] If the user makes any changes to the draft, the changes are sent back to the server, which receives the changes and generates a new draft. This process is repeated until the user is satisfied.

[0055] 7. Save the Final Draft

[0056] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[0057] Specific examples

[0058] User Input

[0059] "Company A supplies goods to Company B every month, and Company B pays for them."

[0060] Server analysis results

[0061] Parties: Company A (supplier), Company B (recipient)

[0062] Product: Any product

[0063] Supply frequency: monthly

[0064] Payment terms: Payment within one month after delivery of goods

[0065] Generated contract draft

[0066] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0067] Article 1 (Supply of Goods)

[0068] The supplier shall provide a monthly supply of any good quality product.

[0069] Article 2 (Payment Terms)

[0070] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0071] Article 3 (Cancellation and Penalty Fees)

[0072] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0073] Comply with legal matters.

[0074] In this way, the system of the present invention automatically analyzes contract content entered by the user in natural language and generates a legally valid contract draft, enabling efficient and accurate contract drafting even for those without legal knowledge.

[0075] The processing flow will be explained below.

[0076] Step 1: The user enters the contract details into the terminal in natural language.

[0077] The user enters the contract details in natural language into the input field on the terminal. For example, "Company A will supply products to Company B every month, and Company B will pay for them."

[0078] Step 2: The device sends the input to the server

[0079] The terminal transmits the contract contents entered by the user in natural language to the server using a secure communication protocol (e.g., HTTPS).

[0080] Step 3: The server passes the input to the natural language processing engine

[0081] The server passes the received contract content in natural language to a natural language processing engine (NLP engine), which performs grammatical and semantic analysis.

[0082] Step 4: Natural language processing engine extracts requirements

[0083] The natural language processing engine extracts the necessary requirements for the contract (e.g., parties, products, payment terms). For example, it extracts "Company A: supplier, Company B: recipient, products: supplied monthly, payment terms: payment within one month after supply."

[0084] Step 5: The server selects a contract template

[0085] The server selects an appropriate contract template from among pre-prepared templates based on the extracted requirements.

[0086] Step 6: The server generates a draft contract

[0087] The server embeds the extracted requirements into the selected template and generates a draft contract, such as "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0088] Step 7: The server sends the generated draft to the device

[0089] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[0090] Step 8: User reviews the draft and makes any necessary revisions

[0091] The terminal displays the received draft and the user checks it. If the user deems it necessary, they can make corrections to the draft, such as amending the payment terms.

[0092] Step 9: The device sends the modifications to the server

[0093] If the user modifies the draft, the device sends the modifications back to the server.

[0094] Step 10: The server regenerates the draft based on the modifications

[0095] The server regenerates a draft contract based on the received amendments, and the regenerated draft is sent to the terminal again.

[0096] Step 11: Review and save the final document

[0097] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[0098] Example 1

[0099] 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."

[0100] Conventional contract creation requires legal knowledge and is time-consuming and labor-intensive. Furthermore, manual contract creation is prone to human error, posing a risk of reducing the accuracy of the contract. Furthermore, revisions and version control are cumbersome, making it difficult to smoothly share contracts with the parties involved. To solve these problems, there is a need for a system that can automatically generate contracts and easily perform revisions and version control.

[0101] 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.

[0102] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content, performing grammatical and semantic analysis, and extracting necessary requirements for a contract, and means for selecting a contract template prepared in advance based on the extracted requirements and generating a contract draft. This makes it possible to automatically generate a contract efficiently and accurately based on the content entered by a user in natural language.

[0103] "User" refers to the entity that uses the system to input and confirm contract documents.

[0104] "Natural language" refers to a language used by humans on a daily basis, not a formal programming language or code.

[0105] "Receiving" is the process of taking information entered by a user and making it available within the system.

[0106] "Grammar analysis" is the process of analyzing the sentence structure of a natural language and identifying the part of speech and role of each word.

[0107] "Semantic analysis" is the process of understanding the meaning of words and phrases identified by grammatical analysis and grasping the meaning of the entire sentence.

[0108] "Contract requirements" refers to the basic information and clauses required for a contract, such as the parties, subject matter of the contract, and payment terms.

[0109] A "template" is a model of a contract, a predetermined document format into which input requirements are embedded.

[0110] A "Draft" is a generated, unfinalized, temporary document of a contract, subject to user review and amendment.

[0111] "Secure" refers to a state in which something is safe and protected from unauthorized access or data tampering.

[0112] "Version control" refers to a system that stores the change history of each version of a contract and allows for comparison and restoration between different versions.

[0113] A "natural language processing engine" is a collection of software and hardware for understanding and analyzing natural language, and performs grammatical analysis, semantic analysis, etc.

[0114] The present invention relates to a system that automatically generates a draft of a contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. Specific embodiments for implementing this system are described below.

[0115] The user enters the contract details in natural language through the device. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them" into a form on the browser. The device then sends the entered details to the server using a secure communication protocol such as HTTPS.

[0116] After receiving the input, the server performs grammatical and semantic analysis using a natural language processing engine (e.g., Google® Cloud Natural Language API or IBM Watson® Natural Language Understanding), thereby extracting the necessary requirements for the contract (e.g., parties, products, and payment terms).

[0117] Next, the server selects an appropriate contract template from among those prepared in advance based on the analysis results and embeds the extracted requirements into the template. For example, it generates a contract draft stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0118] The generated draft is sent from the server to the device, which displays it to the user. The user reviews the draft and makes any necessary corrections. The corrected content is then sent back from the device to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[0119] The finalized draft of the contract is securely stored on the server. The server uses a database (e.g., MySQL (registered trademark), PostgreSQL) to manage contract versions. It also provides a function that makes it easy to share and download contracts.

[0120] For example, if a user enters "Company A will supply goods to Company B every month, and Company B will pay for them" into a browser form and clicks the submit button, the following draft will be generated:

[0121] User Input

[0122] "Company A supplies goods to Company B every month, and Company B pays for them."

[0123] Server analysis results

[0124] Parties: Supplier (Company A), Recipient (Company B)

[0125] Product: Any product

[0126] Supply frequency: monthly

[0127] Payment terms: Payment within one month after delivery of goods

[0128] Generated contract draft

[0129] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0130] Article 1 (Supply of Goods)

[0131] The supplier shall provide a monthly supply of any good quality product.

[0132] Article 2 (Payment Terms)

[0133] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0134] Article 3 (Cancellation and Penalty Fees)

[0135] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0136] Comply with legal matters.

[0137] This system makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] Step 1: User Input

[0140] The user enters the contract details in natural language into the input field on the device. Specifically, the user enters the following into a form on the browser: "Company A will supply products to Company B every month, and Company B will pay for them." The input data is saved in text format on the device.

[0141] Input: User inputs contract details in natural language

[0142] Output: Save natural language text data to your device

[0143] Step 2: Receiving input

[0144] The terminal receives the contract details entered by the user in natural language and sends them to the server using a secure communication protocol such as HTTPS. Specifically, the terminal uses JavaScript (registered trademark) to send the input data to the server via an HTTP POST request.

[0145] Input: User's natural language text data

[0146] Output: Text data sent to the server

[0147] Step 3: Natural Language Analysis

[0148] The server passes the received contract content in natural language to a natural language processing engine (such as Google Cloud Natural Language API or IBM Watson Natural Language Understanding) for grammatical and semantic analysis. Specifically, the analysis engine analyzes the contract content and extracts the requirements necessary for the contract (parties, products, payment terms).

[0149] Input: Natural language text data received by the server

[0150] Output: Extraction results of requirements required for the contract (data in JSON format)

[0151] Step 4: Generate a draft

[0152] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. Specifically, it uses a Python script to run a template engine (e.g., Jinja2) and embeds the contract contents.

[0153] Input: Extraction results of requirements required for the contract

[0154] Output: Generated contract draft (text format)

[0155] Step 5: View the draft

[0156] The generated draft is sent from the server to the device, which then displays it to the user. Specifically, the draft is formatted using HTML and CSS and displayed in the browser. The user can view the displayed draft and perform operations such as scrolling and copy and paste.

[0157] Input: Generated contract draft

[0158] Output: A draft contract displayed in a browser

[0159] Step 6: Receive and regenerate corrections

[0160] If the user makes any changes to the draft, the changes are sent back to the server. Specifically, the device uses JavaScript to collect the changes and sends them back to the server as an HTTP POST request. The server receives the changes and generates a new draft.

[0161] Input: User modifications

[0162] Output: Regenerated draft with corrections

[0163] Step 7: Save the final draft

[0164] The final draft of the contract finalized by the user is stored securely on the server. The server uses a database (e.g., MySQL, PostgreSQL) to manage contract versions. It also provides functionality that makes it easy to share and download contracts. When the user clicks the download link, a PDF version of the contract is generated.

[0165] Input: Finalized contract draft

[0166] Output: Contract saved in database and PDF download link

[0167] (Application example 1)

[0168] 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."

[0169] Conventional contract drafting requires advanced legal knowledge and effort, and is even more difficult when it comes to specialized content such as contracts for the supply of factory robots. This situation hinders the efficient and accurate drafting of contracts and slows down business processes. The present invention aims to solve these problems and provide a method for easily drafting contracts in natural language.

[0170] 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.

[0171] In this invention, the server includes: means for receiving content entered by a user in natural language; means for analyzing the received natural language content and extracting contract requirements; means for generating a draft contract based on the extracted requirements; means for displaying the generated draft to the user; means for receiving content revised by the user again and generating a final contract draft; means for receiving content entered in natural language from a smartphone and transmitting the data to the server; means for analyzing the contract content, extracting requirements, and generating a draft contract by embedding them in a pre-prepared template; means for transmitting the generated draft from the server to the smartphone and displaying it to the user; means for transmitting content revised by the user again to the server and regenerating the contract reflecting the revisions; means for saving the finalized draft contract on the server; and means for generating a draft contract including information on the supplier and recipient, supply items, and payment terms. This enables efficient and accurate automatic generation of contracts regardless of legal knowledge or skills.

[0172] "User" means a person or company that uses the system to create a contract.

[0173] "Natural language" refers to a language used by humans on a daily basis, not a specialized programming language.

[0174] A "smartphone" is a type of mobile phone that can connect to the Internet and run applications.

[0175] A "server" is a computer system that provides services to clients over a network.

[0176] A "draft contract" is an early version of a document describing the contents of a contract, and is a preliminary document before becoming a final contract.

[0177] A "natural language processing engine" is a computer program that analyzes and understands the meaning of natural language used by humans.

[0178] "Requirements" refer to the essential items or clauses that must be included in the contract.

[0179] A "template" is a document with a predetermined format or structure for generating a draft contract.

[0180] "Supplier" refers to the party that supplies goods or services.

[0181] "Recipient" means the party receiving goods or services.

[0182] "Supplied Items" means goods or services provided by a Supplier to a Recipient.

[0183] "Payment terms" refers to the amount to be paid for the supplied items, the payment deadline, payment method, and other terms.

[0184] The present invention relates to a system that allows users to input contract details in natural language using a smartphone and automatically generates a draft contract based on that content. The contract details entered by the user via the smartphone are sent to a server, where they are analyzed by a natural language processing engine. A draft contract is then generated based on the analysis results and displayed to the user. A specific implementation method for this system is described below.

[0185] First, the user enters the contract details in natural language through a dedicated smartphone app. For example, the details might be something like, "The supplier will supply parts to the recipient every month, and the recipient will pay for them." The app then sends this information to the server. Secure communication protocols such as HTTPS are used for safe data transfer.

[0186] The server then passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis. Natural language processing engines such as spaCy and BERT can be used. This analysis extracts the necessary contract terms (parties, products / services, payment terms, etc.).

[0187] Next, based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. This automatically generates a draft contract. For example, the generated draft may look like the one below.

[0188] This Agreement is between the Supplier (hereinafter referred to as the "Supplier") and the Recipient (hereinafter referred to as the "Recipient"). The Supplier will supply parts (hereinafter referred to as the "Parts") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for the Parts.

[0189] The generated draft is sent from the server to the smartphone and displayed to the user. The user checks the displayed draft and makes corrections as necessary. If corrections are made, the content is sent again to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[0190] The finalized draft of the contract is securely stored on the server. A database system is used for this storage. The saved draft of the contract can be easily referenced and updated in the future. It is also possible to manage versions of the contract and share it with the relevant parties.

[0191] Examples:

[0192] User Input: "The supplier will supply the parts to the recipient every month and the recipient will pay for them."

[0193] Example prompt sentence:

[0194] Factory C supplies fuel in engine terminals to Factory D every day, and Factory D pays for it.

[0195] By inputting these specific examples and prompt sentences, a draft contract is automatically generated, allowing for the efficient creation of legally valid contracts. This system makes it possible to create accurate contracts even without specialized knowledge.

[0196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0197] Step 1: The user launches the smartphone app and enters the contract details in natural language.

[0198] The user launches the smartphone application and enters the contract details in a designated input field in natural language. For example, the user might enter, "The supplier will supply parts to the recipient every month, and the recipient will pay for them."

[0199] (Input) Contract details in natural language

[0200] (Output) Confirming user input on a smartphone

[0201] Step 2: The smartphone receives the user's input and sends it to the server.

[0202] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using the HTTPS protocol for secure data transfer.

[0203] (Input) The contract contents entered by the user in natural language

[0204] (Output) Secure data transmission to the server

[0205] Step 3: The server passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis.

[0206] The server passes the received natural language contract content to a natural language processing engine (e.g., spaCy, BERT), which performs grammatical and semantic analysis to extract the necessary contract terms (parties, products / services, payment terms).

[0207] (Input) Contract details in natural language

[0208] (Output) Extraction of contract requirements (e.g., supplier, recipient, supply items, payment terms)

[0209] Step 4: Based on the analysis results, the server selects an appropriate contract template from among the pre-prepared ones, embeds the requirements into the template, and generates a draft contract.

[0210] The server selects a contract template based on the extracted requirements and generates a draft contract by embedding the requirements in the template.

[0211] (Input) Contract requirements based on analysis results

[0212] (Output) Draft contract

[0213] Step 5: The server sends the generated draft to the smartphone and displays it to the user.

[0214] The server sends the generated draft of the contract to the smartphone, which displays it to the user, who can then review the draft and make any necessary corrections.

[0215] (Input) Draft contract

[0216] (Output) Display of drafts that users can see

[0217] Step 6: The user makes revisions to the draft and submits it to the server again.

[0218] The user makes corrections to the displayed draft and sends the corrections back to the server. The terminal receives the corrections and sends them back to the server.

[0219] (Input) User-modified contract details

[0220] (Output) Sending the modified data to the server

[0221] Step 7: The server receives the modifications and generates the draft again.

[0222] The server receives the amendments, analyzes them again using a natural language processing engine, and creates a re-drafted contract. This process is repeated until the user is satisfied.

[0223] (Input) User-modified contract details

[0224] (Output) Regenerated draft agreement

[0225] Step 8: The server saves the finalized draft of the contract.

[0226] The finalized draft of the contract is securely stored in a database system on the server, making it easy to refer to and update in the future. It also allows for version control of the contract and sharing with the relevant parties.

[0227] (Input) Finalized draft of contract

[0228] (Output) Save the draft to the server

[0229] 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.

[0230] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. An embodiment of the present invention includes a process for analyzing the user's input, extracting contract requirements, and reflecting the user's emotional data in the generated contract draft. The system of the present invention incorporates an emotion engine in addition to a natural language processing engine, and has the ability to recognize the user's emotions and appropriately adjust the content of the contract.

[0231] A natural language description of what the program does

[0232] 1. Obtaining user input and emotion data

[0233] The user enters the contract details in natural language into the input field on the device. At the same time, the device acquires emotional data from the user's input. For example, "Company A will supply products to Company B every month, and Company B will pay for them," and also acquires emotional data such as the user's stress level and joy.

[0234] 2. Sending input and emotional data

[0235] The terminal transmits the contract details entered by the user in natural language and the acquired emotion data to the server using a secure communication protocol (e.g., HTTPS).

[0236] 3. Natural Language Analysis

[0237] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[0238] 4. Emotion Data Analysis

[0239] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[0240] 5. Draft generation and adjustment

[0241] Based on the analysis results, the server selects an appropriate contract template from pre-prepared ones and embeds the extracted requirements into the template. It also adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adjusts the content of the contract to be concise and clear.

[0242] 6. Viewing Drafts

[0243] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[0244] 7. Receiving and Regenerating Modifications

[0245] If the user makes any changes to the draft, the changes are sent back to the server, which then receives the changes, adjusts them based on the emotion data, and generates a new draft. This process is repeated until the user is satisfied.

[0246] 8. Save the Final Draft

[0247] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[0248] Specific examples

[0249] User Input and Emotional Data

[0250] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[0251] Emotional data: High stress levels

[0252] Server analysis results

[0253] Parties: Company A (supplier), Company B (recipient)

[0254] Product: Any product

[0255] Supply frequency: monthly

[0256] Payment terms: Payment within one month after delivery of goods

[0257] Emotional state: Stress

[0258] Generated contract draft

[0259] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0260] Article 1 (Supply of Goods)

[0261] The supplier shall provide a monthly supply of any good quality product.

[0262] Article 2 (Payment Terms)

[0263] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0264] Article 3 (Cancellation and Penalty Fees)

[0265] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0266] Comply with legal matters.

[0267] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[0268] The processing flow will be explained below.

[0269] Step 1: The user enters the contract details into the terminal in natural language.

[0270] The user enters the contract details in natural language into the device's input field. For example, "Company A will supply products to Company B every month, and Company B will pay for them." The device also obtains the user's emotional data from this input.

[0271] Step 2: The device sends the input and emotion data to the server.

[0272] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS).

[0273] Step 3: The server parses the natural language content

[0274] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, supply items, payment terms).

[0275] Step 4: The server analyzes the emotion data

[0276] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state, for example, determining whether the user is feeling stressed.

[0277] Step 5: The server generates a draft contract

[0278] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. At the same time, the server adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[0279] Step 6: The server sends the generated draft to the device

[0280] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[0281] Step 7: The device displays the draft, and the user can review and edit it.

[0282] The terminal displays the received draft to the user, who then checks the displayed draft and makes any necessary corrections, such as "change payment terms."

[0283] Step 8: The device sends the modifications to the server

[0284] If the user modifies the draft, the device sends the modifications to the server.

[0285] Step 9: The server regenerates the draft based on the modifications

[0286] The server re-generates a draft contract based on the received revisions. At this time, the emotional state is re-analyzed using the emotion engine, and an adjusted draft is re-generated. The re-generated draft is then sent back to the terminal.

[0287] Step 10: Review and save the final draft

[0288] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[0289] Through each of the above processing steps, the system of the present invention efficiently creates and amends a legally valid contract draft based on the contract content and emotion data entered by the user in natural language, and safely stores the final contract.

[0290] Example 2

[0291] 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."

[0292] Conventional contract drafting systems require advanced legal knowledge to accurately analyze contract content entered by users in natural language and generate appropriate contract drafts. Furthermore, they are unable to take the user's emotional state into account, resulting in poor usability. In particular, when users draft contracts while feeling stressed or anxious, their emotions can affect the content of the contract, resulting in the risk of an inaccurate contract being generated. This makes it difficult to efficiently draft legally valid and user-friendly contracts.

[0293] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0294] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content and extracting contract requirements, means for acquiring emotion data, means for generating a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content revised by the user again and generating a final contract draft, and means for saving the final contract draft. This makes it possible to generate a contract draft that is accurate, legally valid, and adjusted to take the user's emotions into consideration, based on the user's natural language input content and emotion data.

[0295] A "user" is a person who provides natural language input to interact with the system and generate a draft contract.

[0296] "Natural language" refers to a language that humans use on a daily basis, and includes text data that has grammar and meaning.

[0297] "Emotional data" refers to data about a user's emotional state obtained when the user provides input, and includes emotional information such as stress level and joy.

[0298] A "natural language processing engine" is software that analyzes natural language text, understands its grammar and meaning, and converts it into structured data.

[0299] An "emotion engine" is software that analyzes emotional data and identifies the user's emotional state.

[0300] A "draft contract" is a preliminary contract document generated based on user input and requirements extracted by the system.

[0301] A "server" is a computer system that receives and processes data sent by a user from a terminal.

[0302] A "terminal" is an electronic device used by a user to provide input.

[0303] "Generate" refers to the system creating new data or documents based on input data.

[0304] "Preserving" refers to keeping generated data and documents available for a long period of time.

[0305] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. This system includes a process that analyzes the user's input, extracts contract requirements, and reflects the user's emotional data in the generated contract draft.

[0306] The system of the present invention comprises the following elements:

[0307] 1. Obtaining user input and emotion data

[0308] The user enters the contract details in natural language into the device's input field. The device simultaneously acquires the user's emotional data (stress level, joy, etc.). To acquire the emotional data, the device uses the device's built-in camera and microphone to analyze facial expressions and tone of voice.

[0309] 2. Sending input and emotional data

[0310] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, the transmitted data may contain the following format: "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[0311] 3. Natural Language Analysis

[0312] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API), which performs grammatical and semantic analysis to extract the necessary requirements for the contract (parties, supply items, payment terms). For example, elements such as "Company A (supplier), Company B (recipient), monthly, payment terms" can be extracted from the input content.

[0313] 4. Emotion Data Analysis

[0314] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[0315] 5. Draft generation and adjustment

[0316] The server selects an appropriate contract template (e.g., a DocuSign template) from among pre-prepared templates based on the analysis results obtained from the natural language processing engine and emotion engine. It then incorporates the extracted requirements into the template and adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[0317] 6. Viewing Drafts

[0318] The generated contract draft is sent from the server to the terminal, which then displays it to the user. The user can review the draft on the screen and, if any corrections are needed, enter the corrections directly into the text field.

[0319] 7. Receiving and Regenerating Modifications

[0320] If the user makes any edits to the draft, the device sends the edits back to the server, which receives the edits, reanalyzes the emotion data if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[0321] 8. Save the Final Draft

[0322] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[0323] Specific examples

[0324] User Input and Emotional Data

[0325] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[0326] Emotional data: High stress levels

[0327] Server analysis results

[0328] Parties: Company A (supplier), Company B (recipient)

[0329] Product: Any product

[0330] Supply frequency: monthly

[0331] Payment terms: Payment within one month after delivery of goods

[0332] Emotional state: Stress

[0333] Generated contract draft

[0334] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0335] Article 1 (Supply of Goods)

[0336] The supplier shall provide a monthly supply of any good quality product.

[0337] Article 2 (Payment Terms)

[0338] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0339] Article 3 (Cancellation and Penalty Fees)

[0340] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0341] Comply with legal matters.

[0342] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[0343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0344] Step 1:

[0345] Capturing user input and emotion data

[0346] The user enters the contract details in natural language into the device's input field. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them." At this time, the device uses its camera and microphone to simultaneously capture emotional data (stress level, joy, etc.) as the user types. For example, the device captures the entered text, as well as facial expression analysis data and tone of voice analysis data.

[0347] Input: Natural language contract content, emotional data

[0348] Output: Received natural language data and emotion data

[0349] Step 2:

[0350] Sending input and emotion data

[0351] The terminal sends the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, data is sent in the form of "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[0352] Input: Received natural language data, emotion data

[0353] Output: Natural language data and emotion data sent to the server

[0354] Step 3:

[0355] Natural Language Analysis

[0356] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API) for grammatical and semantic analysis, which extracts the necessary requirements for the contract. For example, the server extracts elements such as "Company A (supplier), Company B (receiver), monthly, payment terms" from the input content.

[0357] Input: Natural language data

[0358] Output: Extracted contract requirements data (parties, supply items, payment terms, etc.)

[0359] Step 4:

[0360] Emotional Data Analysis

[0361] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[0362] Input: Emotion data

[0363] Output: Emotion analysis result data (e.g., high stress level)

[0364] Step 5:

[0365] Draft generation and adjustment

[0366] The server uses the analysis results from the natural language processing engine and emotion engine to select an appropriate contract template (e.g., a DocuSign template) from among the pre-prepared templates, and incorporates the extracted requirements into the template. Furthermore, the server adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[0367] Input: Extracted contract requirements data, sentiment analysis result data

[0368] Output: Adjusted draft contract

[0369] Step 6:

[0370] View Drafts

[0371] The generated contract draft is sent from the server to the terminal, which displays the draft to the user, who can then check the draft on the screen. For example, the user can check the contract contents and identify any necessary revisions.

[0372] Input: Adjusted contract draft

[0373] Output: A draft of the contract displayed on the device

[0374] Step 7:

[0375] Receive and regenerate corrections

[0376] If the user makes any changes to the draft, the device sends the changes back to the server, which receives the changes, re-analyzes them if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[0377] Input: User modifications

[0378] Output: Final regenerated contract draft

[0379] Step 8:

[0380] Save the final draft

[0381] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[0382] Input: Final contract draft

[0383] Output: A draft contract saved on the server

[0384] The above is the flow of processing in the system of the present invention.

[0385] (Application example 2)

[0386] 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."

[0387] Conventional contract creation systems simply reflected the content entered by the user in natural language, and the quality of the final contract was often affected by the user's emotional state and the accuracy of the input. This led to issues with inconsistent quality of the final contract. In particular, when users were stressed or tired, input errors and unclear expressions increased, which could cause contract issues. Furthermore, the lack of a user-friendly interface for instantly entering and adjusting contract content on-site made it difficult to operate in factories and other workplaces.

[0388] 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.

[0389] In this invention, the server includes means for receiving content input in natural language by a user, means for analyzing the received natural language content and extracting contract requirements, means for generating and adjusting a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content modified by the user again and generating a final contract draft, means for saving the final contract draft, means for acquiring the input content and emotion data via smart glasses or a head-mounted display used for generating and adjusting the contract draft, and means for using a secure communication protocol to transmit data to a remote server. This enables the generation of an optimal contract draft according to the user's emotional state, enabling rapid and high-quality contract creation on the factory floor.

[0390] "User" means a person who uses the system to create or modify a contract.

[0391] "Natural language" refers to a language that humans use on a daily basis and is used to input contract details.

[0392] "Emotional data" is data that expresses a user's emotional state in numerical or categorical terms, including stress levels, joy, etc.

[0393] "Contract requirements" are the basic information and clauses that should be included in the contract, such as the parties, items to be supplied, and payment terms.

[0394] A "draft" is a preliminary agreement prepared before the final agreement.

[0395] "Smart glasses" are glasses-type wearable devices equipped with a display and sensors and capable of displaying information using AR technology.

[0396] A "head-mounted display (HMD)" is a display device worn on the head that directly displays visual information.

[0397] A "secure communication protocol" is a communication protocol for securely sending and receiving data, and includes HTTPS.

[0398] A "natural language processing engine (NLP engine)" is a software module for analyzing natural language and understanding its meaning.

[0399] An "emotion analysis engine" is a software module that analyzes a user's emotional data and determines their emotional state.

[0400] A "remote server" is a server device that contains computer resources and data at a remote location that can be accessed via a network.

[0401] "Contract disputes" refer to disputes or problems between the parties that arise due to misunderstandings or non-performance of the contractual terms.

[0402] "Factory floor" refers to the physical facility or location where goods are manufactured or production activities take place.

[0403] A system embodying the present invention includes the following elements for quickly and accurately creating contracts on the factory floor:

[0404] Hardware and Software

[0405] Hardware: Smart glasses or head-mounted displays (HMDs) act as interfaces to receive user input. These devices are used by users to enter contract details. Additionally, these devices monitor and collect data on the user's emotional state.

[0406] Software: Natural language processing engine (NLP engine) and sentiment analysis engine. These engines run on the server and analyze the natural language and sentiment data entered by the user.

[0407] Program processing

[0408] 1. Obtaining user input and emotion data

[0409] The user inputs the contract details in natural language via smart glasses or an HMD, while the device simultaneously captures the user's emotional data (e.g., stress level and happiness).

[0410] 2. Sending input and emotional data

[0411] The contract details entered by the user in natural language and the acquired emotional data are sent to the server using a secure communication protocol (HTTPS).

[0412] 3. Server Analysis

[0413] The server passes the received natural language content to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[0414] The server then passes the received emotional data to an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[0415] 4. Contract draft generation and adjustment

[0416] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. It also adjusts the content and wording of the contract based on the results of the sentiment analysis. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[0417] 5. View and edit drafts

[0418] The generated contract draft is sent from the server to the device and displayed to the user through smart glasses or an HMD, where the user can review the displayed draft and make any necessary corrections.

[0419] Specific examples

[0420] Example user input: "Company A supplies goods to Company B every month, and Company B pays for them."

[0421] Emotional data: User's stress level is high

[0422] Server analysis results

[0423] Parties: Company A (supplier), Company B (recipient)

[0424] Product: Any product

[0425] Supply frequency: monthly

[0426] Payment terms: Payment within one month after delivery of goods

[0427] Emotional state: User is under high stress

[0428] Generated Agreement Draft:

[0429] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0430] Article 1 (Supply of Goods)

[0431] The supplier shall provide a monthly supply of high quality concise goods.

[0432] Article 2 (Payment Terms)

[0433] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0434] Article 3 (Cancellation and Penalty Fees)

[0435] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0436] Comply with legal matters.

[0437] Example prompt for a generative AI model:

[0438] "Company A will supply products to Company B every month, and Company B will pay for them. This is causing users a lot of stress. Please write the contract succinctly and clearly, and automatically generate a draft."

[0439] In this way, by using this system, users can generate optimal contract drafts according to their emotional state, enabling fast and high-quality contract creation on the factory floor.

[0440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0441] Step 1:

[0442] The user inputs the contract details in natural language via smart glasses or a head-mounted display. The input data includes the contract details text and emotional data. The emotional data includes the user's stress level and happiness. As a result, the device acquires the contract details and emotional data.

[0443] Step 2:

[0444] The device transmits the acquired natural language contract details and emotion data to the server using a secure communication protocol (HTTPS). This transmission process ensures that the data is delivered to the server safely. The input includes the user's contract details text and emotion data, and the output is the data sent to the server.

[0445] Step 3:

[0446] The server passes the received contract text to a natural language processing engine (NLP engine) for grammatical and semantic analysis. Specifically, it extracts the necessary contract requirements, such as the parties, supply items, and payment terms, from the input contract text. The input contains the contract text, and the extracted requirements are obtained as the output.

[0447] Step 4:

[0448] The server passes the received emotional data to the emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the data is analyzed. The input contains emotional data, and the output is a result about the user's emotional state.

[0449] Step 5:

[0450] The server selects an appropriate contract template from pre-prepared ones based on the analyzed contract requirements and emotional data, and generates a contract draft. The content and wording of the contract are adjusted based on the results of the emotional analysis. For example, if the user is feeling stressed, the content of the contract is adjusted to be concise and clear. The input includes the extracted contract requirements and the results of the emotional state, and the adjusted contract draft is generated as the output.

[0451] Step 6:

[0452] The generated contract draft is sent from the server to the terminal via smart glasses or a head-mounted display and displayed to the user. The user can check the displayed draft and make any necessary corrections. The input includes the contract draft, and the output is the user's confirmation and corrections.

[0453] Step 7:

[0454] If the user modifies the draft contract, the modifications are sent from the device to the server again. The server receives the modifications, analyzes and adjusts them again, and generates the final draft. This process is repeated until the user is satisfied. The input contains the user's modifications, and the output is the final draft contract.

[0455] Step 8:

[0456] The finalized contract draft is securely stored on the server for easy future reference and updating. This allows contract version control and sharing with stakeholders. The input includes the final contract draft, and the output is secure storage of the contract.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] [Second embodiment]

[0461] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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).

[0467] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0468] 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.

[0469] 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.

[0470] 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.

[0471] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0472] 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."

[0473] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. An embodiment of the present invention includes a process in which a user enters contract content in natural language via a terminal, and the input content is analyzed by a server and generated as a draft contract.

[0474] A natural language description of what the program does

[0475] 1. User Input

[0476] The user enters the contract details in natural language into the input field on the terminal. For example, they enter something like "Company A will supply products to Company B every month, and Company B will pay for them."

[0477] 2. Receiving input

[0478] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using a secure communication protocol such as HTTPS.

[0479] 3. Natural Language Analysis

[0480] The server passes the received contract content in natural language to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, products, payment terms).

[0481] 4. Generate a draft

[0482] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and generates a draft contract by embedding the extracted requirements into the template. For example, a draft contract may be generated stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0483] 5. Viewing Drafts

[0484] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[0485] 6. Receiving and Regenerating Modifications

[0486] If the user makes any changes to the draft, the changes are sent back to the server, which receives the changes and generates a new draft. This process is repeated until the user is satisfied.

[0487] 7. Save the Final Draft

[0488] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[0489] Specific examples

[0490] User Input

[0491] "Company A supplies goods to Company B every month, and Company B pays for them."

[0492] Server analysis results

[0493] Parties: Company A (supplier), Company B (recipient)

[0494] Product: Any product

[0495] Supply frequency: monthly

[0496] Payment terms: Payment within one month after delivery of goods

[0497] Generated contract draft

[0498] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0499] Article 1 (Supply of Goods)

[0500] The supplier shall provide a monthly supply of any good quality product.

[0501] Article 2 (Payment Terms)

[0502] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0503] Article 3 (Cancellation and Penalty Fees)

[0504] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0505] Comply with legal matters.

[0506] In this way, the system of the present invention automatically analyzes contract content entered by the user in natural language and generates a legally valid contract draft, enabling efficient and accurate contract drafting even for those without legal knowledge.

[0507] The processing flow will be explained below.

[0508] Step 1: The user enters the contract details into the terminal in natural language.

[0509] The user enters the contract details in natural language into the input field on the terminal. For example, "Company A will supply products to Company B every month, and Company B will pay for them."

[0510] Step 2: The device sends the input to the server

[0511] The terminal transmits the contract contents entered by the user in natural language to the server using a secure communication protocol (e.g., HTTPS).

[0512] Step 3: The server passes the input to the natural language processing engine

[0513] The server passes the received contract content in natural language to a natural language processing engine (NLP engine), which performs grammatical and semantic analysis.

[0514] Step 4: Natural language processing engine extracts requirements

[0515] The natural language processing engine extracts the necessary requirements for the contract (e.g., parties, products, payment terms). For example, it extracts "Company A: supplier, Company B: recipient, products: supplied monthly, payment terms: payment within one month after supply."

[0516] Step 5: The server selects a contract template

[0517] The server selects an appropriate contract template from among pre-prepared templates based on the extracted requirements.

[0518] Step 6: The server generates a draft contract

[0519] The server embeds the extracted requirements into the selected template and generates a draft contract, such as "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0520] Step 7: The server sends the generated draft to the device

[0521] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[0522] Step 8: User reviews the draft and makes any necessary revisions

[0523] The terminal displays the received draft and the user checks it. If the user deems it necessary, they can make corrections to the draft, such as amending the payment terms.

[0524] Step 9: The device sends the modifications to the server

[0525] If the user modifies the draft, the device sends the modifications back to the server.

[0526] Step 10: The server regenerates the draft based on the modifications

[0527] The server regenerates a draft contract based on the received amendments, and the regenerated draft is sent to the terminal again.

[0528] Step 11: Review and save the final document

[0529] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[0530] Example 1

[0531] 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."

[0532] Conventional contract creation requires legal knowledge and is time-consuming and labor-intensive. Furthermore, manual contract creation is prone to human error, posing a risk of reducing the accuracy of the contract. Furthermore, revisions and version control are cumbersome, making it difficult to smoothly share contracts with the parties involved. To solve these problems, there is a need for a system that can automatically generate contracts and easily perform revisions and version control.

[0533] 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.

[0534] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content, performing grammatical and semantic analysis, and extracting necessary requirements for a contract, and means for selecting a contract template prepared in advance based on the extracted requirements and generating a contract draft. This makes it possible to automatically generate a contract efficiently and accurately based on the content entered by a user in natural language.

[0535] "User" refers to the entity that uses the system to input and confirm contract documents.

[0536] "Natural language" refers to a language used by humans on a daily basis, not a formal programming language or code.

[0537] "Receiving" is the process of taking information entered by a user and making it available within the system.

[0538] "Grammar analysis" is the process of analyzing the sentence structure of a natural language and identifying the part of speech and role of each word.

[0539] "Semantic analysis" is the process of understanding the meaning of words and phrases identified by grammatical analysis and grasping the meaning of the entire sentence.

[0540] "Contract requirements" refers to the basic information and clauses required for a contract, such as the parties, subject matter of the contract, and payment terms.

[0541] A "template" is a model of a contract, a predetermined document format into which input requirements are embedded.

[0542] A "Draft" is a generated, unfinalized, temporary document of a contract, subject to user review and amendment.

[0543] "Secure" refers to a state in which something is safe and protected from unauthorized access or data tampering.

[0544] "Version control" refers to a system that stores the change history of each version of a contract and allows for comparison and restoration between different versions.

[0545] A "natural language processing engine" is a collection of software and hardware for understanding and analyzing natural language, and performs grammatical analysis, semantic analysis, etc.

[0546] The present invention relates to a system that automatically generates a draft of a contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. Specific embodiments for implementing this system are described below.

[0547] The user enters the contract details in natural language through the device. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them" into a form on the browser. The device then sends the entered details to the server using a secure communication protocol such as HTTPS.

[0548] After receiving the input, the server performs grammatical and semantic analysis using a natural language processing engine (e.g., Google Cloud Natural Language API or IBM Watson Natural Language Understanding), which extracts the necessary requirements for the contract (e.g., parties, products, and payment terms).

[0549] Next, the server selects an appropriate contract template from among those prepared in advance based on the analysis results and embeds the extracted requirements into the template. For example, it generates a contract draft stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0550] The generated draft is sent from the server to the device, which displays it to the user. The user reviews the draft and makes any necessary corrections. The corrected content is then sent back from the device to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[0551] The finalized draft of the contract is securely stored on the server, which uses a database (e.g., MySQL or PostgreSQL) to manage contract versions and also provides functionality to easily share and download contracts.

[0552] For example, if a user enters "Company A will supply goods to Company B every month, and Company B will pay for them" into a browser form and clicks the submit button, the following draft will be generated:

[0553] User Input

[0554] "Company A supplies goods to Company B every month, and Company B pays for them."

[0555] Server analysis results

[0556] Parties: Supplier (Company A), Recipient (Company B)

[0557] Product: Any product

[0558] Supply frequency: monthly

[0559] Payment terms: Payment within one month after delivery of goods

[0560] Generated contract draft

[0561] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0562] Article 1 (Supply of Goods)

[0563] The supplier shall provide a monthly supply of any good quality product.

[0564] Article 2 (Payment Terms)

[0565] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0566] Article 3 (Cancellation and Penalty Fees)

[0567] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0568] Comply with legal matters.

[0569] This system makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[0570] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0571] Step 1: User Input

[0572] The user enters the contract details in natural language into the input field on the device. Specifically, the user enters the following into a form on the browser: "Company A will supply products to Company B every month, and Company B will pay for them." The input data is saved in text format on the device.

[0573] Input: User inputs contract details in natural language

[0574] Output: Save natural language text data to your device

[0575] Step 2: Receiving input

[0576] The terminal receives the contract details entered by the user in natural language and sends them to the server using a secure communication protocol such as HTTPS. Specifically, JavaScript is used to send the input data to the server via an HTTP POST request.

[0577] Input: User's natural language text data

[0578] Output: Text data sent to the server

[0579] Step 3: Natural Language Analysis

[0580] The server passes the received contract content in natural language to a natural language processing engine (such as Google Cloud Natural Language API or IBM Watson Natural Language Understanding) for grammatical and semantic analysis. Specifically, the analysis engine analyzes the contract content and extracts the requirements necessary for the contract (parties, products, payment terms).

[0581] Input: Natural language text data received by the server

[0582] Output: Extraction results of requirements required for the contract (data in JSON format)

[0583] Step 4: Generate a draft

[0584] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. Specifically, it uses a Python script to run a template engine (e.g., Jinja2) and embeds the contract contents.

[0585] Input: Extraction results of requirements required for the contract

[0586] Output: Generated contract draft (text format)

[0587] Step 5: View the draft

[0588] The generated draft is sent from the server to the device, which then displays it to the user. Specifically, the draft is formatted using HTML and CSS and displayed in the browser. The user can view the displayed draft and perform operations such as scrolling and copy and paste.

[0589] Input: Generated contract draft

[0590] Output: A draft contract displayed in a browser

[0591] Step 6: Receive and regenerate corrections

[0592] If the user makes any changes to the draft, the changes are sent back to the server. Specifically, the device uses JavaScript to collect the changes and sends them back to the server as an HTTP POST request. The server receives the changes and generates a new draft.

[0593] Input: User modifications

[0594] Output: Regenerated draft with corrections

[0595] Step 7: Save the final draft

[0596] The final draft of the contract finalized by the user is stored securely on the server. The server uses a database (e.g., MySQL, PostgreSQL) to manage contract versions. It also provides functionality that makes it easy to share and download contracts. When the user clicks the download link, a PDF version of the contract is generated.

[0597] Input: Finalized contract draft

[0598] Output: Contract saved in database and PDF download link

[0599] (Application example 1)

[0600] 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."

[0601] Conventional contract drafting requires advanced legal knowledge and effort, and is even more difficult when it comes to specialized content such as contracts for the supply of factory robots. This situation hinders the efficient and accurate drafting of contracts and slows down business processes. The present invention aims to solve these problems and provide a method for easily drafting contracts in natural language.

[0602] 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.

[0603] In this invention, the server includes: means for receiving content entered by a user in natural language; means for analyzing the received natural language content and extracting contract requirements; means for generating a draft contract based on the extracted requirements; means for displaying the generated draft to the user; means for receiving content revised by the user again and generating a final contract draft; means for receiving content entered in natural language from a smartphone and transmitting the data to the server; means for analyzing the contract content, extracting requirements, and generating a draft contract by embedding them in a pre-prepared template; means for transmitting the generated draft from the server to the smartphone and displaying it to the user; means for transmitting content revised by the user again to the server and regenerating the contract reflecting the revisions; means for saving the finalized draft contract on the server; and means for generating a draft contract including information on the supplier and recipient, supply items, and payment terms. This enables efficient and accurate automatic generation of contracts regardless of legal knowledge or skills.

[0604] "User" means a person or company that uses the system to create a contract.

[0605] "Natural language" refers to a language used by humans on a daily basis, not a specialized programming language.

[0606] A "smartphone" is a type of mobile phone that can connect to the Internet and run applications.

[0607] A "server" is a computer system that provides services to clients over a network.

[0608] A "draft contract" is an early version of a document describing the contents of a contract, and is a preliminary document before becoming a final contract.

[0609] A "natural language processing engine" is a computer program that analyzes and understands the meaning of natural language used by humans.

[0610] "Requirements" refer to the essential items or clauses that must be included in the contract.

[0611] A "template" is a document with a predetermined format or structure for generating a draft contract.

[0612] "Supplier" refers to the party that supplies goods or services.

[0613] "Recipient" means the party receiving goods or services.

[0614] "Supplied Items" means goods or services provided by a Supplier to a Recipient.

[0615] "Payment terms" refers to the amount to be paid for the supplied items, the payment deadline, payment method, and other terms.

[0616] The present invention relates to a system that allows users to input contract details in natural language using a smartphone and automatically generates a draft contract based on that content. The contract details entered by the user via the smartphone are sent to a server, where they are analyzed by a natural language processing engine. A draft contract is then generated based on the analysis results and displayed to the user. A specific implementation method for this system is described below.

[0617] First, the user enters the contract details in natural language through a dedicated smartphone app. For example, the details might be something like, "The supplier will supply parts to the recipient every month, and the recipient will pay for them." The app then sends this information to the server. Secure communication protocols such as HTTPS are used for safe data transfer.

[0618] The server then passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis. Natural language processing engines such as spaCy and BERT can be used. This analysis extracts the necessary contract terms (parties, products / services, payment terms, etc.).

[0619] Next, based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. This automatically generates a draft contract. For example, the generated draft may look like the one below.

[0620] This Agreement is between the Supplier (hereinafter referred to as the "Supplier") and the Recipient (hereinafter referred to as the "Recipient"). The Supplier will supply parts (hereinafter referred to as the "Parts") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for the Parts.

[0621] The generated draft is sent from the server to the smartphone and displayed to the user. The user checks the displayed draft and makes corrections as necessary. If corrections are made, the content is sent again to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[0622] The finalized draft of the contract is securely stored on the server. A database system is used for this storage. The saved draft of the contract can be easily referenced and updated in the future. It is also possible to manage versions of the contract and share it with the relevant parties.

[0623] Examples:

[0624] User Input: "The supplier will supply the parts to the recipient every month and the recipient will pay for them."

[0625] Example prompt sentence:

[0626] Factory C supplies fuel in engine terminals to Factory D every day, and Factory D pays for it.

[0627] By inputting these specific examples and prompt sentences, a draft contract is automatically generated, allowing for the efficient creation of legally valid contracts. This system makes it possible to create accurate contracts even without specialized knowledge.

[0628] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0629] Step 1: The user launches the smartphone app and enters the contract details in natural language.

[0630] The user launches the smartphone application and enters the contract details in a designated input field in natural language. For example, the user might enter, "The supplier will supply parts to the recipient every month, and the recipient will pay for them."

[0631] (Input) Contract details in natural language

[0632] (Output) Confirming user input on a smartphone

[0633] Step 2: The smartphone receives the user's input and sends it to the server.

[0634] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using the HTTPS protocol for secure data transfer.

[0635] (Input) The contract contents entered by the user in natural language

[0636] (Output) Secure data transmission to the server

[0637] Step 3: The server passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis.

[0638] The server passes the received natural language contract content to a natural language processing engine (e.g., spaCy, BERT), which performs grammatical and semantic analysis to extract the necessary contract terms (parties, products / services, payment terms).

[0639] (Input) Contract details in natural language

[0640] (Output) Extraction of contract requirements (e.g., supplier, recipient, supply items, payment terms)

[0641] Step 4: Based on the analysis results, the server selects an appropriate contract template from among the pre-prepared ones, embeds the requirements into the template, and generates a draft contract.

[0642] The server selects a contract template based on the extracted requirements and generates a draft contract by embedding the requirements in the template.

[0643] (Input) Contract requirements based on analysis results

[0644] (Output) Draft contract

[0645] Step 5: The server sends the generated draft to the smartphone and displays it to the user.

[0646] The server sends the generated draft of the contract to the smartphone, which displays it to the user, who can then review the draft and make any necessary corrections.

[0647] (Input) Draft contract

[0648] (Output) Display of drafts that users can see

[0649] Step 6: The user makes revisions to the draft and submits it to the server again.

[0650] The user makes corrections to the displayed draft and sends the corrections back to the server. The terminal receives the corrections and sends them back to the server.

[0651] (Input) User-modified contract details

[0652] (Output) Sending the modified data to the server

[0653] Step 7: The server receives the modifications and generates the draft again.

[0654] The server receives the amendments, analyzes them again using a natural language processing engine, and creates a re-drafted contract. This process is repeated until the user is satisfied.

[0655] (Input) User-modified contract details

[0656] (Output) Regenerated draft agreement

[0657] Step 8: The server saves the finalized draft of the contract.

[0658] The finalized draft of the contract is securely stored in a database system on the server, making it easy to refer to and update in the future. It also allows for version control of the contract and sharing with the relevant parties.

[0659] (Input) Finalized draft of contract

[0660] (Output) Save the draft to the server

[0661] 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.

[0662] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. An embodiment of the present invention includes a process for analyzing the user's input, extracting contract requirements, and reflecting the user's emotional data in the generated contract draft. The system of the present invention incorporates an emotion engine in addition to a natural language processing engine, and has the ability to recognize the user's emotions and appropriately adjust the content of the contract.

[0663] A natural language description of what the program does

[0664] 1. Obtaining user input and emotion data

[0665] The user enters the contract details in natural language into the input field on the device. At the same time, the device acquires emotional data from the user's input. For example, "Company A will supply products to Company B every month, and Company B will pay for them," and also acquires emotional data such as the user's stress level and joy.

[0666] 2. Sending input and emotional data

[0667] The terminal transmits the contract details entered by the user in natural language and the acquired emotion data to the server using a secure communication protocol (e.g., HTTPS).

[0668] 3. Natural Language Analysis

[0669] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[0670] 4. Emotion Data Analysis

[0671] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[0672] 5. Draft generation and adjustment

[0673] Based on the analysis results, the server selects an appropriate contract template from pre-prepared ones and embeds the extracted requirements into the template. It also adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adjusts the content of the contract to be concise and clear.

[0674] 6. Viewing Drafts

[0675] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[0676] 7. Receiving and Regenerating Modifications

[0677] If the user makes any changes to the draft, the changes are sent back to the server, which then receives the changes, adjusts them based on the emotion data, and generates a new draft. This process is repeated until the user is satisfied.

[0678] 8. Save the Final Draft

[0679] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[0680] Specific examples

[0681] User Input and Emotional Data

[0682] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[0683] Emotional data: High stress levels

[0684] Server analysis results

[0685] Parties: Company A (supplier), Company B (recipient)

[0686] Product: Any product

[0687] Supply frequency: monthly

[0688] Payment terms: Payment within one month after delivery of goods

[0689] Emotional state: Stress

[0690] Generated contract draft

[0691] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0692] Article 1 (Supply of Goods)

[0693] The supplier shall provide a monthly supply of any good quality product.

[0694] Article 2 (Payment Terms)

[0695] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0696] Article 3 (Cancellation and Penalty Fees)

[0697] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0698] Comply with legal matters.

[0699] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[0700] The processing flow will be explained below.

[0701] Step 1: The user enters the contract details into the terminal in natural language.

[0702] The user enters the contract details in natural language into the device's input field. For example, "Company A will supply products to Company B every month, and Company B will pay for them." The device also obtains the user's emotional data from this input.

[0703] Step 2: The device sends the input and emotion data to the server.

[0704] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS).

[0705] Step 3: The server parses the natural language content

[0706] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, supply items, payment terms).

[0707] Step 4: The server analyzes the emotion data

[0708] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state, for example, determining whether the user is feeling stressed.

[0709] Step 5: The server generates a draft contract

[0710] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. At the same time, the server adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[0711] Step 6: The server sends the generated draft to the device

[0712] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[0713] Step 7: The device displays the draft, and the user can review and edit it.

[0714] The terminal displays the received draft to the user, who then checks the displayed draft and makes any necessary corrections, such as "change payment terms."

[0715] Step 8: The device sends the modifications to the server

[0716] If the user modifies the draft, the device sends the modifications to the server.

[0717] Step 9: The server regenerates the draft based on the modifications

[0718] The server re-generates a draft contract based on the received revisions. At this time, the emotional state is re-analyzed using the emotion engine, and an adjusted draft is re-generated. The re-generated draft is then sent back to the terminal.

[0719] Step 10: Review and save the final draft

[0720] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[0721] Through each of the above processing steps, the system of the present invention efficiently creates and amends a legally valid contract draft based on the contract content and emotion data entered by the user in natural language, and safely stores the final contract.

[0722] Example 2

[0723] 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."

[0724] Conventional contract drafting systems require advanced legal knowledge to accurately analyze contract content entered by users in natural language and generate appropriate contract drafts. Furthermore, they are unable to take the user's emotional state into account, resulting in poor usability. In particular, when users draft contracts while feeling stressed or anxious, their emotions can affect the content of the contract, resulting in the risk of an inaccurate contract being generated. This makes it difficult to efficiently draft legally valid and user-friendly contracts.

[0725] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0726] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content and extracting contract requirements, means for acquiring emotion data, means for generating a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content revised by the user again and generating a final contract draft, and means for saving the final contract draft. This makes it possible to generate a contract draft that is accurate, legally valid, and adjusted to take the user's emotions into consideration, based on the user's natural language input content and emotion data.

[0727] A "user" is a person who provides natural language input to interact with the system and generate a draft contract.

[0728] "Natural language" refers to a language that humans use on a daily basis, and includes text data that has grammar and meaning.

[0729] "Emotional data" refers to data about a user's emotional state obtained when the user provides input, and includes emotional information such as stress level and joy.

[0730] A "natural language processing engine" is software that analyzes natural language text, understands its grammar and meaning, and converts it into structured data.

[0731] An "emotion engine" is software that analyzes emotional data and identifies the user's emotional state.

[0732] A "draft contract" is a preliminary contract document generated based on user input and requirements extracted by the system.

[0733] A "server" is a computer system that receives and processes data sent by a user from a terminal.

[0734] A "terminal" is an electronic device used by a user to provide input.

[0735] "Generate" refers to the system creating new data or documents based on input data.

[0736] "Preserving" refers to keeping generated data and documents available for a long period of time.

[0737] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. This system includes a process that analyzes the user's input, extracts contract requirements, and reflects the user's emotional data in the generated contract draft.

[0738] The system of the present invention comprises the following elements:

[0739] 1. Obtaining user input and emotion data

[0740] The user enters the contract details in natural language into the device's input field. The device simultaneously acquires the user's emotional data (stress level, joy, etc.). To acquire the emotional data, the device uses the device's built-in camera and microphone to analyze facial expressions and tone of voice.

[0741] 2. Sending input and emotional data

[0742] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, the transmitted data may contain the following format: "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[0743] 3. Natural Language Analysis

[0744] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API), which performs grammatical and semantic analysis to extract the necessary requirements for the contract (parties, supply items, payment terms). For example, elements such as "Company A (supplier), Company B (recipient), monthly, payment terms" can be extracted from the input content.

[0745] 4. Emotion Data Analysis

[0746] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[0747] 5. Draft generation and adjustment

[0748] The server selects an appropriate contract template (e.g., a DocuSign template) from among pre-prepared templates based on the analysis results obtained from the natural language processing engine and emotion engine. It then incorporates the extracted requirements into the template and adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[0749] 6. Viewing Drafts

[0750] The generated contract draft is sent from the server to the terminal, which then displays it to the user. The user can review the draft on the screen and, if any corrections are needed, enter the corrections directly into the text field.

[0751] 7. Receiving and Regenerating Modifications

[0752] If the user makes any edits to the draft, the device sends the edits back to the server, which receives the edits, reanalyzes the emotion data if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[0753] 8. Save the Final Draft

[0754] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[0755] Specific examples

[0756] User Input and Emotional Data

[0757] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[0758] Emotional data: High stress levels

[0759] Server analysis results

[0760] Parties: Company A (supplier), Company B (recipient)

[0761] Product: Any product

[0762] Supply frequency: monthly

[0763] Payment terms: Payment within one month after delivery of goods

[0764] Emotional state: Stress

[0765] Generated contract draft

[0766] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0767] Article 1 (Supply of Goods)

[0768] The supplier shall provide a monthly supply of any good quality product.

[0769] Article 2 (Payment Terms)

[0770] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0771] Article 3 (Cancellation and Penalty Fees)

[0772] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0773] Comply with legal matters.

[0774] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[0775] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0776] Step 1:

[0777] Capturing user input and emotion data

[0778] The user enters the contract details in natural language into the device's input field. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them." At this time, the device uses its camera and microphone to simultaneously capture emotional data (stress level, joy, etc.) as the user types. For example, the device captures the entered text, as well as facial expression analysis data and tone of voice analysis data.

[0779] Input: Natural language contract content, emotional data

[0780] Output: Received natural language data and emotion data

[0781] Step 2:

[0782] Sending input and emotion data

[0783] The terminal sends the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, data is sent in the form of "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[0784] Input: Received natural language data, emotion data

[0785] Output: Natural language data and emotion data sent to the server

[0786] Step 3:

[0787] Natural Language Analysis

[0788] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API) for grammatical and semantic analysis, which extracts the necessary requirements for the contract. For example, the server extracts elements such as "Company A (supplier), Company B (receiver), monthly, payment terms" from the input content.

[0789] Input: Natural language data

[0790] Output: Extracted contract requirements data (parties, supply items, payment terms, etc.)

[0791] Step 4:

[0792] Emotional Data Analysis

[0793] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[0794] Input: Emotion data

[0795] Output: Emotion analysis result data (e.g., high stress level)

[0796] Step 5:

[0797] Draft generation and adjustment

[0798] The server uses the analysis results from the natural language processing engine and emotion engine to select an appropriate contract template (e.g., a DocuSign template) from among the pre-prepared templates, and incorporates the extracted requirements into the template. Furthermore, the server adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[0799] Input: Extracted contract requirements data, sentiment analysis result data

[0800] Output: Adjusted draft contract

[0801] Step 6:

[0802] View Drafts

[0803] The generated contract draft is sent from the server to the terminal, which displays the draft to the user, who can then check the draft on the screen. For example, the user can check the contract contents and identify any necessary revisions.

[0804] Input: Adjusted contract draft

[0805] Output: A draft of the contract displayed on the device

[0806] Step 7:

[0807] Receive and regenerate corrections

[0808] If the user makes any changes to the draft, the device sends the changes back to the server, which receives the changes, re-analyzes them if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[0809] Input: User modifications

[0810] Output: Final regenerated contract draft

[0811] Step 8:

[0812] Save the final draft

[0813] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[0814] Input: Final contract draft

[0815] Output: A draft contract saved on the server

[0816] The above is the flow of processing in the system of the present invention.

[0817] (Application example 2)

[0818] 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."

[0819] Conventional contract creation systems simply reflected the content entered by the user in natural language, and the quality of the final contract was often affected by the user's emotional state and the accuracy of the input. This led to issues with inconsistent quality of the final contract. In particular, when users were stressed or tired, input errors and unclear expressions increased, which could cause contract issues. Furthermore, the lack of a user-friendly interface for instantly entering and adjusting contract content on-site made it difficult to operate in factories and other workplaces.

[0820] 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.

[0821] In this invention, the server includes means for receiving content input in natural language by a user, means for analyzing the received natural language content and extracting contract requirements, means for generating and adjusting a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content modified by the user again and generating a final contract draft, means for saving the final contract draft, means for acquiring the input content and emotion data via smart glasses or a head-mounted display used for generating and adjusting the contract draft, and means for using a secure communication protocol to transmit data to a remote server. This enables the generation of an optimal contract draft according to the user's emotional state, enabling rapid and high-quality contract creation on the factory floor.

[0822] "User" means a person who uses the system to create or modify a contract.

[0823] "Natural language" refers to a language that humans use on a daily basis and is used to input contract details.

[0824] "Emotional data" is data that expresses a user's emotional state in numerical or categorical terms, including stress levels, joy, etc.

[0825] "Contract requirements" are the basic information and clauses that should be included in the contract, such as the parties, items to be supplied, and payment terms.

[0826] A "draft" is a preliminary agreement prepared before the final agreement.

[0827] "Smart glasses" are glasses-type wearable devices equipped with a display and sensors and capable of displaying information using AR technology.

[0828] A "head-mounted display (HMD)" is a display device worn on the head that directly displays visual information.

[0829] A "secure communication protocol" is a communication protocol for securely sending and receiving data, and includes HTTPS.

[0830] A "natural language processing engine (NLP engine)" is a software module for analyzing natural language and understanding its meaning.

[0831] An "emotion analysis engine" is a software module that analyzes a user's emotional data and determines their emotional state.

[0832] A "remote server" is a server device that contains computer resources and data at a remote location that can be accessed via a network.

[0833] "Contract disputes" refer to disputes or problems between the parties that arise due to misunderstandings or non-performance of the contractual terms.

[0834] "Factory floor" refers to the physical facility or location where goods are manufactured or production activities take place.

[0835] A system embodying the present invention includes the following elements for quickly and accurately creating contracts on the factory floor:

[0836] Hardware and Software

[0837] Hardware: Smart glasses or head-mounted displays (HMDs) act as interfaces to receive user input. These devices are used by users to enter contract details. Additionally, these devices monitor and collect data on the user's emotional state.

[0838] Software: Natural language processing engine (NLP engine) and sentiment analysis engine. These engines run on the server and analyze the natural language and sentiment data entered by the user.

[0839] Program processing

[0840] 1. Obtaining user input and emotion data

[0841] The user inputs the contract details in natural language via smart glasses or an HMD, while the device simultaneously captures the user's emotional data (e.g., stress level and happiness).

[0842] 2. Sending input and emotional data

[0843] The contract details entered by the user in natural language and the acquired emotional data are sent to the server using a secure communication protocol (HTTPS).

[0844] 3. Server Analysis

[0845] The server passes the received natural language content to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[0846] The server then passes the received emotional data to an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[0847] 4. Contract draft generation and adjustment

[0848] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. It also adjusts the content and wording of the contract based on the results of the sentiment analysis. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[0849] 5. View and edit drafts

[0850] The generated contract draft is sent from the server to the device and displayed to the user through smart glasses or an HMD, where the user can review the displayed draft and make any necessary corrections.

[0851] Specific examples

[0852] Example user input: "Company A supplies goods to Company B every month, and Company B pays for them."

[0853] Emotional data: User's stress level is high

[0854] Server analysis results

[0855] Parties: Company A (supplier), Company B (recipient)

[0856] Product: Any product

[0857] Supply frequency: monthly

[0858] Payment terms: Payment within one month after delivery of goods

[0859] Emotional state: User is under high stress

[0860] Generated Agreement Draft:

[0861] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0862] Article 1 (Supply of Goods)

[0863] The supplier shall provide a monthly supply of high quality concise goods.

[0864] Article 2 (Payment Terms)

[0865] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0866] Article 3 (Cancellation and Penalty Fees)

[0867] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0868] Comply with legal matters.

[0869] Example prompt for a generative AI model:

[0870] "Company A will supply products to Company B every month, and Company B will pay for them. This is causing users a lot of stress. Please write the contract succinctly and clearly, and automatically generate a draft."

[0871] In this way, by using this system, users can generate optimal contract drafts according to their emotional state, enabling fast and high-quality contract creation on the factory floor.

[0872] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0873] Step 1:

[0874] The user inputs the contract details in natural language via smart glasses or a head-mounted display. The input data includes the contract details text and emotional data. The emotional data includes the user's stress level and happiness. As a result, the device acquires the contract details and emotional data.

[0875] Step 2:

[0876] The device transmits the acquired natural language contract details and emotion data to the server using a secure communication protocol (HTTPS). This transmission process ensures that the data is delivered to the server safely. The input includes the user's contract details text and emotion data, and the output is the data sent to the server.

[0877] Step 3:

[0878] The server passes the received contract text to a natural language processing engine (NLP engine) for grammatical and semantic analysis. Specifically, it extracts the necessary contract requirements, such as the parties, supply items, and payment terms, from the input contract text. The input contains the contract text, and the extracted requirements are obtained as the output.

[0879] Step 4:

[0880] The server passes the received emotional data to the emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the data is analyzed. The input contains emotional data, and the output is a result about the user's emotional state.

[0881] Step 5:

[0882] The server selects an appropriate contract template from pre-prepared ones based on the analyzed contract requirements and emotional data, and generates a contract draft. The content and wording of the contract are adjusted based on the results of the emotional analysis. For example, if the user is feeling stressed, the content of the contract is adjusted to be concise and clear. The input includes the extracted contract requirements and the results of the emotional state, and the adjusted contract draft is generated as the output.

[0883] Step 6:

[0884] The generated contract draft is sent from the server to the terminal via smart glasses or a head-mounted display and displayed to the user. The user can check the displayed draft and make any necessary corrections. The input includes the contract draft, and the output is the user's confirmation and corrections.

[0885] Step 7:

[0886] If the user modifies the draft contract, the modifications are sent from the device to the server again. The server receives the modifications, analyzes and adjusts them again, and generates the final draft. This process is repeated until the user is satisfied. The input contains the user's modifications, and the output is the final draft contract.

[0887] Step 8:

[0888] The finalized contract draft is securely stored on the server for easy future reference and updating. This allows contract version control and sharing with stakeholders. The input includes the final contract draft, and the output is secure storage of the contract.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] [Third embodiment]

[0893] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0894] 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.

[0895] 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).

[0896] 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.

[0897] 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.

[0898] 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).

[0899] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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."

[0905] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. An embodiment of the present invention includes a process in which a user enters contract content in natural language via a terminal, and the input content is analyzed by a server and generated as a draft contract.

[0906] A natural language description of what the program does

[0907] 1. User Input

[0908] The user enters the contract details in natural language into the input field on the terminal. For example, they enter something like "Company A will supply products to Company B every month, and Company B will pay for them."

[0909] 2. Receiving input

[0910] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using a secure communication protocol such as HTTPS.

[0911] 3. Natural Language Analysis

[0912] The server passes the received contract content in natural language to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, products, payment terms).

[0913] 4. Generate a draft

[0914] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and generates a draft contract by embedding the extracted requirements into the template. For example, a draft contract may be generated stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0915] 5. Viewing Drafts

[0916] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[0917] 6. Receiving and Regenerating Modifications

[0918] If the user makes any changes to the draft, the changes are sent back to the server, which receives the changes and generates a new draft. This process is repeated until the user is satisfied.

[0919] 7. Save the Final Draft

[0920] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[0921] Specific examples

[0922] User Input

[0923] "Company A supplies goods to Company B every month, and Company B pays for them."

[0924] Server analysis results

[0925] Parties: Company A (supplier), Company B (recipient)

[0926] Product: Any product

[0927] Supply frequency: monthly

[0928] Payment terms: Payment within one month after delivery of goods

[0929] Generated contract draft

[0930] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0931] Article 1 (Supply of Goods)

[0932] The supplier shall provide a monthly supply of any good quality product.

[0933] Article 2 (Payment Terms)

[0934] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0935] Article 3 (Cancellation and Penalty Fees)

[0936] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[0937] Comply with legal matters.

[0938] In this way, the system of the present invention automatically analyzes contract content entered by the user in natural language and generates a legally valid contract draft, enabling efficient and accurate contract drafting even for those without legal knowledge.

[0939] The processing flow will be explained below.

[0940] Step 1: The user enters the contract details into the terminal in natural language.

[0941] The user enters the contract details in natural language into the input field on the terminal. For example, "Company A will supply products to Company B every month, and Company B will pay for them."

[0942] Step 2: The device sends the input to the server

[0943] The terminal transmits the contract contents entered by the user in natural language to the server using a secure communication protocol (e.g., HTTPS).

[0944] Step 3: The server passes the input to the natural language processing engine

[0945] The server passes the received contract content in natural language to a natural language processing engine (NLP engine), which performs grammatical and semantic analysis.

[0946] Step 4: Natural language processing engine extracts requirements

[0947] The natural language processing engine extracts the necessary requirements for the contract (e.g., parties, products, payment terms). For example, it extracts "Company A: supplier, Company B: recipient, products: supplied monthly, payment terms: payment within one month after supply."

[0948] Step 5: The server selects a contract template

[0949] The server selects an appropriate contract template from among pre-prepared templates based on the extracted requirements.

[0950] Step 6: The server generates a draft contract

[0951] The server embeds the extracted requirements into the selected template and generates a draft contract, such as "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0952] Step 7: The server sends the generated draft to the device

[0953] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[0954] Step 8: User reviews the draft and makes any necessary revisions

[0955] The terminal displays the received draft and the user checks it. If the user deems it necessary, they can make corrections to the draft, such as amending the payment terms.

[0956] Step 9: The device sends the modifications to the server

[0957] If the user modifies the draft, the device sends the modifications back to the server.

[0958] Step 10: The server regenerates the draft based on the modifications

[0959] The server regenerates a draft contract based on the received amendments, and the regenerated draft is sent to the terminal again.

[0960] Step 11: Review and save the final document

[0961] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[0962] Example 1

[0963] 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."

[0964] Conventional contract creation requires legal knowledge and is time-consuming and labor-intensive. Furthermore, manual contract creation is prone to human error, posing a risk of reducing the accuracy of the contract. Furthermore, revisions and version control are cumbersome, making it difficult to smoothly share contracts with the parties involved. To solve these problems, there is a need for a system that can automatically generate contracts and easily perform revisions and version control.

[0965] 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.

[0966] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content, performing grammatical and semantic analysis, and extracting necessary requirements for a contract, and means for selecting a contract template prepared in advance based on the extracted requirements and generating a contract draft. This makes it possible to automatically generate a contract efficiently and accurately based on the content entered by a user in natural language.

[0967] "User" refers to the entity that uses the system to input and confirm contract documents.

[0968] "Natural language" refers to a language used by humans on a daily basis, not a formal programming language or code.

[0969] "Receiving" is the process of taking information entered by a user and making it available within the system.

[0970] "Grammar analysis" is the process of analyzing the sentence structure of a natural language and identifying the part of speech and role of each word.

[0971] "Semantic analysis" is the process of understanding the meaning of words and phrases identified by grammatical analysis and grasping the meaning of the entire sentence.

[0972] "Contract requirements" refers to the basic information and clauses required for a contract, such as the parties, subject matter of the contract, and payment terms.

[0973] A "template" is a model of a contract, a predetermined document format into which input requirements are embedded.

[0974] A "Draft" is a generated, unfinalized, temporary document of a contract, subject to user review and amendment.

[0975] "Secure" refers to a state in which something is safe and protected from unauthorized access or data tampering.

[0976] "Version control" refers to a system that stores the change history of each version of a contract and allows for comparison and restoration between different versions.

[0977] A "natural language processing engine" is a collection of software and hardware for understanding and analyzing natural language, and performs grammatical analysis, semantic analysis, etc.

[0978] The present invention relates to a system that automatically generates a draft of a contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. Specific embodiments for implementing this system are described below.

[0979] The user enters the contract details in natural language through the device. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them" into a form on the browser. The device then sends the entered details to the server using a secure communication protocol such as HTTPS.

[0980] After receiving the input, the server performs grammatical and semantic analysis using a natural language processing engine (e.g., Google Cloud Natural Language API or IBM Watson Natural Language Understanding), which extracts the necessary requirements for the contract (e.g., parties, products, and payment terms).

[0981] Next, the server selects an appropriate contract template from among those prepared in advance based on the analysis results and embeds the extracted requirements into the template. For example, it generates a contract draft stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[0982] The generated draft is sent from the server to the device, which displays it to the user. The user reviews the draft and makes any necessary corrections. The corrected content is then sent back from the device to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[0983] The finalized draft of the contract is securely stored on the server, which uses a database (e.g., MySQL or PostgreSQL) to manage contract versions and also provides functionality to easily share and download contracts.

[0984] For example, if a user enters "Company A will supply goods to Company B every month, and Company B will pay for them" into a browser form and clicks the submit button, the following draft will be generated:

[0985] User Input

[0986] "Company A supplies goods to Company B every month, and Company B pays for them."

[0987] Server analysis results

[0988] Parties: Supplier (Company A), Recipient (Company B)

[0989] Product: Any product

[0990] Supply frequency: monthly

[0991] Payment terms: Payment within one month after delivery of goods

[0992] Generated contract draft

[0993] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[0994] Article 1 (Supply of Goods)

[0995] The supplier shall provide a monthly supply of any good quality product.

[0996] Article 2 (Payment Terms)

[0997] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[0998] Article 3 (Cancellation and Penalty Fees)

[0999] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1000] Comply with legal matters.

[1001] This system makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[1002] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1003] Step 1: User Input

[1004] The user enters the contract details in natural language into the input field on the device. Specifically, the user enters the following into a form on the browser: "Company A will supply products to Company B every month, and Company B will pay for them." The input data is saved in text format on the device.

[1005] Input: User inputs contract details in natural language

[1006] Output: Save natural language text data to your device

[1007] Step 2: Receiving input

[1008] The terminal receives the contract details entered by the user in natural language and sends them to the server using a secure communication protocol such as HTTPS. Specifically, JavaScript is used to send the input data to the server via an HTTP POST request.

[1009] Input: User's natural language text data

[1010] Output: Text data sent to the server

[1011] Step 3: Natural Language Analysis

[1012] The server passes the received contract content in natural language to a natural language processing engine (such as Google Cloud Natural Language API or IBM Watson Natural Language Understanding) for grammatical and semantic analysis. Specifically, the analysis engine analyzes the contract content and extracts the requirements necessary for the contract (parties, products, payment terms).

[1013] Input: Natural language text data received by the server

[1014] Output: Extraction results of requirements required for the contract (data in JSON format)

[1015] Step 4: Generate a draft

[1016] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. Specifically, it uses a Python script to run a template engine (e.g., Jinja2) and embeds the contract contents.

[1017] Input: Extraction results of requirements required for the contract

[1018] Output: Generated contract draft (text format)

[1019] Step 5: View the draft

[1020] The generated draft is sent from the server to the device, which then displays it to the user. Specifically, the draft is formatted using HTML and CSS and displayed in the browser. The user can view the displayed draft and perform operations such as scrolling and copy and paste.

[1021] Input: Generated contract draft

[1022] Output: A draft contract displayed in a browser

[1023] Step 6: Receive and regenerate corrections

[1024] If the user makes any changes to the draft, the changes are sent back to the server. Specifically, the device uses JavaScript to collect the changes and sends them back to the server as an HTTP POST request. The server receives the changes and generates a new draft.

[1025] Input: User modifications

[1026] Output: Regenerated draft with corrections

[1027] Step 7: Save the final draft

[1028] The final draft of the contract finalized by the user is stored securely on the server. The server uses a database (e.g., MySQL, PostgreSQL) to manage contract versions. It also provides functionality that makes it easy to share and download contracts. When the user clicks the download link, a PDF version of the contract is generated.

[1029] Input: Finalized contract draft

[1030] Output: Contract saved in database and PDF download link

[1031] (Application example 1)

[1032] 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."

[1033] Conventional contract drafting requires advanced legal knowledge and effort, and is even more difficult when it comes to specialized content such as contracts for the supply of factory robots. This situation hinders the efficient and accurate drafting of contracts and slows down business processes. The present invention aims to solve these problems and provide a method for easily drafting contracts in natural language.

[1034] 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.

[1035] In this invention, the server includes: means for receiving content entered by a user in natural language; means for analyzing the received natural language content and extracting contract requirements; means for generating a draft contract based on the extracted requirements; means for displaying the generated draft to the user; means for receiving content revised by the user again and generating a final contract draft; means for receiving content entered in natural language from a smartphone and transmitting the data to the server; means for analyzing the contract content, extracting requirements, and generating a draft contract by embedding them in a pre-prepared template; means for transmitting the generated draft from the server to the smartphone and displaying it to the user; means for transmitting content revised by the user again to the server and regenerating the contract reflecting the revisions; means for saving the finalized draft contract on the server; and means for generating a draft contract including information on the supplier and recipient, supply items, and payment terms. This enables efficient and accurate automatic generation of contracts regardless of legal knowledge or skills.

[1036] "User" means a person or company that uses the system to create a contract.

[1037] "Natural language" refers to a language used by humans on a daily basis, not a specialized programming language.

[1038] A "smartphone" is a type of mobile phone that can connect to the Internet and run applications.

[1039] A "server" is a computer system that provides services to clients over a network.

[1040] A "draft contract" is an early version of a document describing the contents of a contract, and is a preliminary document before becoming a final contract.

[1041] A "natural language processing engine" is a computer program that analyzes and understands the meaning of natural language used by humans.

[1042] "Requirements" refer to the essential items or clauses that must be included in the contract.

[1043] A "template" is a document with a predetermined format or structure for generating a draft contract.

[1044] "Supplier" refers to the party that supplies goods or services.

[1045] "Recipient" means the party receiving goods or services.

[1046] "Supplied Items" means goods or services provided by a Supplier to a Recipient.

[1047] "Payment terms" refers to the amount to be paid for the supplied items, the payment deadline, payment method, and other terms.

[1048] The present invention relates to a system that allows users to input contract details in natural language using a smartphone and automatically generates a draft contract based on that content. The contract details entered by the user via the smartphone are sent to a server, where they are analyzed by a natural language processing engine. A draft contract is then generated based on the analysis results and displayed to the user. A specific implementation method for this system is described below.

[1049] First, the user enters the contract details in natural language through a dedicated smartphone app. For example, the details might be something like, "The supplier will supply parts to the recipient every month, and the recipient will pay for them." The app then sends this information to the server. Secure communication protocols such as HTTPS are used for safe data transfer.

[1050] The server then passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis. Natural language processing engines such as spaCy and BERT can be used. This analysis extracts the necessary contract terms (parties, products / services, payment terms, etc.).

[1051] Next, based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. This automatically generates a draft contract. For example, the generated draft may look like the one below.

[1052] This Agreement is between the Supplier (hereinafter referred to as the "Supplier") and the Recipient (hereinafter referred to as the "Recipient"). The Supplier will supply parts (hereinafter referred to as the "Parts") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for the Parts.

[1053] The generated draft is sent from the server to the smartphone and displayed to the user. The user checks the displayed draft and makes corrections as necessary. If corrections are made, the content is sent again to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[1054] The finalized draft of the contract is securely stored on the server. A database system is used for this storage. The saved draft of the contract can be easily referenced and updated in the future. It is also possible to manage versions of the contract and share it with the relevant parties.

[1055] Examples:

[1056] User Input: "The supplier will supply the parts to the recipient every month and the recipient will pay for them."

[1057] Example prompt sentence:

[1058] Factory C supplies fuel in engine terminals to Factory D every day, and Factory D pays for it.

[1059] By inputting these specific examples and prompt sentences, a draft contract is automatically generated, allowing for the efficient creation of legally valid contracts. This system makes it possible to create accurate contracts even without specialized knowledge.

[1060] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1061] Step 1: The user launches the smartphone app and enters the contract details in natural language.

[1062] The user launches the smartphone application and enters the contract details in a designated input field in natural language. For example, the user might enter, "The supplier will supply parts to the recipient every month, and the recipient will pay for them."

[1063] (Input) Contract details in natural language

[1064] (Output) Confirming user input on a smartphone

[1065] Step 2: The smartphone receives the user's input and sends it to the server.

[1066] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using the HTTPS protocol for secure data transfer.

[1067] (Input) The contract contents entered by the user in natural language

[1068] (Output) Secure data transmission to the server

[1069] Step 3: The server passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis.

[1070] The server passes the received natural language contract content to a natural language processing engine (e.g., spaCy, BERT), which performs grammatical and semantic analysis to extract the necessary contract terms (parties, products / services, payment terms).

[1071] (Input) Contract details in natural language

[1072] (Output) Extraction of contract requirements (e.g., supplier, recipient, supply items, payment terms)

[1073] Step 4: Based on the analysis results, the server selects an appropriate contract template from among the pre-prepared ones, embeds the requirements into the template, and generates a draft contract.

[1074] The server selects a contract template based on the extracted requirements and generates a draft contract by embedding the requirements in the template.

[1075] (Input) Contract requirements based on analysis results

[1076] (Output) Draft contract

[1077] Step 5: The server sends the generated draft to the smartphone and displays it to the user.

[1078] The server sends the generated draft of the contract to the smartphone, which displays it to the user, who can then review the draft and make any necessary corrections.

[1079] (Input) Draft contract

[1080] (Output) Display of drafts that users can see

[1081] Step 6: The user makes revisions to the draft and submits it to the server again.

[1082] The user makes corrections to the displayed draft and sends the corrections back to the server. The terminal receives the corrections and sends them back to the server.

[1083] (Input) User-modified contract details

[1084] (Output) Sending the modified data to the server

[1085] Step 7: The server receives the modifications and generates the draft again.

[1086] The server receives the amendments, analyzes them again using a natural language processing engine, and creates a re-drafted contract. This process is repeated until the user is satisfied.

[1087] (Input) User-modified contract details

[1088] (Output) Regenerated draft agreement

[1089] Step 8: The server saves the finalized draft of the contract.

[1090] The finalized draft of the contract is securely stored in a database system on the server, making it easy to refer to and update in the future. It also allows for version control of the contract and sharing with the relevant parties.

[1091] (Input) Finalized draft of contract

[1092] (Output) Save the draft to the server

[1093] 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.

[1094] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. An embodiment of the present invention includes a process for analyzing the user's input, extracting contract requirements, and reflecting the user's emotional data in the generated contract draft. The system of the present invention incorporates an emotion engine in addition to a natural language processing engine, and has the ability to recognize the user's emotions and appropriately adjust the content of the contract.

[1095] A natural language description of what the program does

[1096] 1. Obtaining user input and emotion data

[1097] The user enters the contract details in natural language into the input field on the device. At the same time, the device acquires emotional data from the user's input. For example, "Company A will supply products to Company B every month, and Company B will pay for them," and also acquires emotional data such as the user's stress level and joy.

[1098] 2. Sending input and emotional data

[1099] The terminal transmits the contract details entered by the user in natural language and the acquired emotion data to the server using a secure communication protocol (e.g., HTTPS).

[1100] 3. Natural Language Analysis

[1101] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[1102] 4. Emotion Data Analysis

[1103] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[1104] 5. Draft generation and adjustment

[1105] Based on the analysis results, the server selects an appropriate contract template from pre-prepared ones and embeds the extracted requirements into the template. It also adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adjusts the content of the contract to be concise and clear.

[1106] 6. Viewing Drafts

[1107] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[1108] 7. Receiving and Regenerating Modifications

[1109] If the user makes any changes to the draft, the changes are sent back to the server, which then receives the changes, adjusts them based on the emotion data, and generates a new draft. This process is repeated until the user is satisfied.

[1110] 8. Save the Final Draft

[1111] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[1112] Specific examples

[1113] User Input and Emotional Data

[1114] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[1115] Emotional data: High stress levels

[1116] Server analysis results

[1117] Parties: Company A (supplier), Company B (recipient)

[1118] Product: Any product

[1119] Supply frequency: monthly

[1120] Payment terms: Payment within one month after delivery of goods

[1121] Emotional state: Stress

[1122] Generated contract draft

[1123] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1124] Article 1 (Supply of Goods)

[1125] The supplier shall provide a monthly supply of any good quality product.

[1126] Article 2 (Payment Terms)

[1127] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1128] Article 3 (Cancellation and Penalty Fees)

[1129] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1130] Comply with legal matters.

[1131] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[1132] The processing flow will be explained below.

[1133] Step 1: The user enters the contract details into the terminal in natural language.

[1134] The user enters the contract details in natural language into the device's input field. For example, "Company A will supply products to Company B every month, and Company B will pay for them." The device also obtains the user's emotional data from this input.

[1135] Step 2: The device sends the input and emotion data to the server.

[1136] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS).

[1137] Step 3: The server parses the natural language content

[1138] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, supply items, payment terms).

[1139] Step 4: The server analyzes the emotion data

[1140] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state, for example, determining whether the user is feeling stressed.

[1141] Step 5: The server generates a draft contract

[1142] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. At the same time, the server adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[1143] Step 6: The server sends the generated draft to the device

[1144] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[1145] Step 7: The device displays the draft, and the user can review and edit it.

[1146] The terminal displays the received draft to the user, who then checks the displayed draft and makes any necessary corrections, such as "change payment terms."

[1147] Step 8: The device sends the modifications to the server

[1148] If the user modifies the draft, the device sends the modifications to the server.

[1149] Step 9: The server regenerates the draft based on the modifications

[1150] The server re-generates a draft contract based on the received revisions. At this time, the emotional state is re-analyzed using the emotion engine, and an adjusted draft is re-generated. The re-generated draft is then sent back to the terminal.

[1151] Step 10: Review and save the final draft

[1152] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[1153] Through each of the above processing steps, the system of the present invention efficiently creates and amends a legally valid contract draft based on the contract content and emotion data entered by the user in natural language, and safely stores the final contract.

[1154] Example 2

[1155] 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."

[1156] Conventional contract drafting systems require advanced legal knowledge to accurately analyze contract content entered by users in natural language and generate appropriate contract drafts. Furthermore, they are unable to take the user's emotional state into account, resulting in poor usability. In particular, when users draft contracts while feeling stressed or anxious, their emotions can affect the content of the contract, resulting in the risk of an inaccurate contract being generated. This makes it difficult to efficiently draft legally valid and user-friendly contracts.

[1157] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1158] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content and extracting contract requirements, means for acquiring emotion data, means for generating a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content revised by the user again and generating a final contract draft, and means for saving the final contract draft. This makes it possible to generate a contract draft that is accurate, legally valid, and adjusted to take the user's emotions into consideration, based on the user's natural language input content and emotion data.

[1159] A "user" is a person who provides natural language input to interact with the system and generate a draft contract.

[1160] "Natural language" refers to a language that humans use on a daily basis, and includes text data that has grammar and meaning.

[1161] "Emotional data" refers to data about a user's emotional state obtained when the user provides input, and includes emotional information such as stress level and joy.

[1162] A "natural language processing engine" is software that analyzes natural language text, understands its grammar and meaning, and converts it into structured data.

[1163] An "emotion engine" is software that analyzes emotional data and identifies the user's emotional state.

[1164] A "draft contract" is a preliminary contract document generated based on user input and requirements extracted by the system.

[1165] A "server" is a computer system that receives and processes data sent by a user from a terminal.

[1166] A "terminal" is an electronic device used by a user to provide input.

[1167] "Generate" refers to the system creating new data or documents based on input data.

[1168] "Preserving" refers to keeping generated data and documents available for a long period of time.

[1169] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. This system includes a process that analyzes the user's input, extracts contract requirements, and reflects the user's emotional data in the generated contract draft.

[1170] The system of the present invention comprises the following elements:

[1171] 1. Obtaining user input and emotion data

[1172] The user enters the contract details in natural language into the device's input field. The device simultaneously acquires the user's emotional data (stress level, joy, etc.). To acquire the emotional data, the device uses the device's built-in camera and microphone to analyze facial expressions and tone of voice.

[1173] 2. Sending input and emotional data

[1174] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, the transmitted data may contain the following format: "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[1175] 3. Natural Language Analysis

[1176] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API), which performs grammatical and semantic analysis to extract the necessary requirements for the contract (parties, supply items, payment terms). For example, elements such as "Company A (supplier), Company B (recipient), monthly, payment terms" can be extracted from the input content.

[1177] 4. Emotion Data Analysis

[1178] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[1179] 5. Draft generation and adjustment

[1180] The server selects an appropriate contract template (e.g., a DocuSign template) from among pre-prepared templates based on the analysis results obtained from the natural language processing engine and emotion engine. It then incorporates the extracted requirements into the template and adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[1181] 6. Viewing Drafts

[1182] The generated contract draft is sent from the server to the terminal, which then displays it to the user. The user can review the draft on the screen and, if any corrections are needed, enter the corrections directly into the text field.

[1183] 7. Receiving and Regenerating Modifications

[1184] If the user makes any edits to the draft, the device sends the edits back to the server, which receives the edits, reanalyzes the emotion data if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[1185] 8. Save the Final Draft

[1186] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[1187] Specific examples

[1188] User Input and Emotional Data

[1189] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[1190] Emotional data: High stress levels

[1191] Server analysis results

[1192] Parties: Company A (supplier), Company B (recipient)

[1193] Product: Any product

[1194] Supply frequency: monthly

[1195] Payment terms: Payment within one month after delivery of goods

[1196] Emotional state: Stress

[1197] Generated contract draft

[1198] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1199] Article 1 (Supply of Goods)

[1200] The supplier shall provide a monthly supply of any good quality product.

[1201] Article 2 (Payment Terms)

[1202] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1203] Article 3 (Cancellation and Penalty Fees)

[1204] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1205] Comply with legal matters.

[1206] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[1207] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1208] Step 1:

[1209] Capturing user input and emotion data

[1210] The user enters the contract details in natural language into the device's input field. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them." At this time, the device uses its camera and microphone to simultaneously capture emotional data (stress level, joy, etc.) as the user types. For example, the device captures the entered text, as well as facial expression analysis data and tone of voice analysis data.

[1211] Input: Natural language contract content, emotional data

[1212] Output: Received natural language data and emotion data

[1213] Step 2:

[1214] Sending input and emotion data

[1215] The terminal sends the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, data is sent in the form of "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[1216] Input: Received natural language data, emotion data

[1217] Output: Natural language data and emotion data sent to the server

[1218] Step 3:

[1219] Natural Language Analysis

[1220] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API) for grammatical and semantic analysis, which extracts the necessary requirements for the contract. For example, the server extracts elements such as "Company A (supplier), Company B (receiver), monthly, payment terms" from the input content.

[1221] Input: Natural language data

[1222] Output: Extracted contract requirements data (parties, supply items, payment terms, etc.)

[1223] Step 4:

[1224] Emotional Data Analysis

[1225] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[1226] Input: Emotion data

[1227] Output: Emotion analysis result data (e.g., high stress level)

[1228] Step 5:

[1229] Draft generation and adjustment

[1230] The server uses the analysis results from the natural language processing engine and emotion engine to select an appropriate contract template (e.g., a DocuSign template) from among the pre-prepared templates, and incorporates the extracted requirements into the template. Furthermore, the server adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[1231] Input: Extracted contract requirements data, sentiment analysis result data

[1232] Output: Adjusted draft contract

[1233] Step 6:

[1234] View Drafts

[1235] The generated contract draft is sent from the server to the terminal, which displays the draft to the user, who can then check the draft on the screen. For example, the user can check the contract contents and identify any necessary revisions.

[1236] Input: Adjusted contract draft

[1237] Output: A draft of the contract displayed on the device

[1238] Step 7:

[1239] Receive and regenerate corrections

[1240] If the user makes any changes to the draft, the device sends the changes back to the server, which receives the changes, re-analyzes them if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[1241] Input: User modifications

[1242] Output: Final regenerated contract draft

[1243] Step 8:

[1244] Save the final draft

[1245] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[1246] Input: Final contract draft

[1247] Output: A draft contract saved on the server

[1248] The above is the flow of processing in the system of the present invention.

[1249] (Application example 2)

[1250] 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."

[1251] Conventional contract creation systems simply reflected the content entered by the user in natural language, and the quality of the final contract was often affected by the user's emotional state and the accuracy of the input. This led to issues with inconsistent quality of the final contract. In particular, when users were stressed or tired, input errors and unclear expressions increased, which could cause contract issues. Furthermore, the lack of a user-friendly interface for instantly entering and adjusting contract content on-site made it difficult to operate in factories and other workplaces.

[1252] 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.

[1253] In this invention, the server includes means for receiving content input in natural language by a user, means for analyzing the received natural language content and extracting contract requirements, means for generating and adjusting a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content modified by the user again and generating a final contract draft, means for saving the final contract draft, means for acquiring the input content and emotion data via smart glasses or a head-mounted display used for generating and adjusting the contract draft, and means for using a secure communication protocol to transmit data to a remote server. This enables the generation of an optimal contract draft according to the user's emotional state, enabling rapid and high-quality contract creation on the factory floor.

[1254] "User" means a person who uses the system to create or modify a contract.

[1255] "Natural language" refers to a language that humans use on a daily basis and is used to input contract details.

[1256] "Emotional data" is data that expresses a user's emotional state in numerical or categorical terms, including stress levels, joy, etc.

[1257] "Contract requirements" are the basic information and clauses that should be included in the contract, such as the parties, items to be supplied, and payment terms.

[1258] A "draft" is a preliminary agreement prepared before the final agreement.

[1259] "Smart glasses" are glasses-type wearable devices equipped with a display and sensors and capable of displaying information using AR technology.

[1260] A "head-mounted display (HMD)" is a display device worn on the head that directly displays visual information.

[1261] A "secure communication protocol" is a communication protocol for securely sending and receiving data, and includes HTTPS.

[1262] A "natural language processing engine (NLP engine)" is a software module for analyzing natural language and understanding its meaning.

[1263] An "emotion analysis engine" is a software module that analyzes a user's emotional data and determines their emotional state.

[1264] A "remote server" is a server device that contains computer resources and data at a remote location that can be accessed via a network.

[1265] "Contract disputes" refer to disputes or problems between the parties that arise due to misunderstandings or non-performance of the contractual terms.

[1266] "Factory floor" refers to the physical facility or location where goods are manufactured or production activities take place.

[1267] A system embodying the present invention includes the following elements for quickly and accurately creating contracts on the factory floor:

[1268] Hardware and Software

[1269] Hardware: Smart glasses or head-mounted displays (HMDs) act as interfaces to receive user input. These devices are used by users to enter contract details. Additionally, these devices monitor and collect data on the user's emotional state.

[1270] Software: Natural language processing engine (NLP engine) and sentiment analysis engine. These engines run on the server and analyze the natural language and sentiment data entered by the user.

[1271] Program processing

[1272] 1. Obtaining user input and emotion data

[1273] The user inputs the contract details in natural language via smart glasses or an HMD, while the device simultaneously captures the user's emotional data (e.g., stress level and happiness).

[1274] 2. Sending input and emotional data

[1275] The contract details entered by the user in natural language and the acquired emotional data are sent to the server using a secure communication protocol (HTTPS).

[1276] 3. Server Analysis

[1277] The server passes the received natural language content to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[1278] The server then passes the received emotional data to an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[1279] 4. Contract draft generation and adjustment

[1280] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. It also adjusts the content and wording of the contract based on the results of the sentiment analysis. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[1281] 5. View and edit drafts

[1282] The generated contract draft is sent from the server to the device and displayed to the user through smart glasses or an HMD, where the user can review the displayed draft and make any necessary corrections.

[1283] Specific examples

[1284] Example user input: "Company A supplies goods to Company B every month, and Company B pays for them."

[1285] Emotional data: User's stress level is high

[1286] Server analysis results

[1287] Parties: Company A (supplier), Company B (recipient)

[1288] Product: Any product

[1289] Supply frequency: monthly

[1290] Payment terms: Payment within one month after delivery of goods

[1291] Emotional state: User is under high stress

[1292] Generated Agreement Draft:

[1293] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1294] Article 1 (Supply of Goods)

[1295] The supplier shall provide a monthly supply of high quality concise goods.

[1296] Article 2 (Payment Terms)

[1297] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1298] Article 3 (Cancellation and Penalty Fees)

[1299] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1300] Comply with legal matters.

[1301] Example prompt for a generative AI model:

[1302] "Company A will supply products to Company B every month, and Company B will pay for them. This is causing users a lot of stress. Please write the contract succinctly and clearly, and automatically generate a draft."

[1303] In this way, by using this system, users can generate optimal contract drafts according to their emotional state, enabling fast and high-quality contract creation on the factory floor.

[1304] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1305] Step 1:

[1306] The user inputs the contract details in natural language via smart glasses or a head-mounted display. The input data includes the contract details text and emotional data. The emotional data includes the user's stress level and happiness. As a result, the device acquires the contract details and emotional data.

[1307] Step 2:

[1308] The device transmits the acquired natural language contract details and emotion data to the server using a secure communication protocol (HTTPS). This transmission process ensures that the data is delivered to the server safely. The input includes the user's contract details text and emotion data, and the output is the data sent to the server.

[1309] Step 3:

[1310] The server passes the received contract text to a natural language processing engine (NLP engine) for grammatical and semantic analysis. Specifically, it extracts the necessary contract requirements, such as the parties, supply items, and payment terms, from the input contract text. The input contains the contract text, and the extracted requirements are obtained as the output.

[1311] Step 4:

[1312] The server passes the received emotional data to the emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the data is analyzed. The input contains emotional data, and the output is a result about the user's emotional state.

[1313] Step 5:

[1314] The server selects an appropriate contract template from pre-prepared ones based on the analyzed contract requirements and emotional data, and generates a contract draft. The content and wording of the contract are adjusted based on the results of the emotional analysis. For example, if the user is feeling stressed, the content of the contract is adjusted to be concise and clear. The input includes the extracted contract requirements and the results of the emotional state, and the adjusted contract draft is generated as the output.

[1315] Step 6:

[1316] The generated contract draft is sent from the server to the terminal via smart glasses or a head-mounted display and displayed to the user. The user can check the displayed draft and make any necessary corrections. The input includes the contract draft, and the output is the user's confirmation and corrections.

[1317] Step 7:

[1318] If the user modifies the draft contract, the modifications are sent from the device to the server again. The server receives the modifications, analyzes and adjusts them again, and generates the final draft. This process is repeated until the user is satisfied. The input contains the user's modifications, and the output is the final draft contract.

[1319] Step 8:

[1320] The finalized contract draft is securely stored on the server for easy future reference and updating. This allows contract version control and sharing with stakeholders. The input includes the final contract draft, and the output is secure storage of the contract.

[1321] 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.

[1322] 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.

[1323] 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.

[1324] [Fourth embodiment]

[1325] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1326] 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.

[1327] 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).

[1328] 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.

[1329] 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.

[1330] 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).

[1331] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1332] 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.

[1333] 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.

[1334] 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.

[1335] 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.

[1336] 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.

[1337] 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."

[1338] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. An embodiment of the present invention includes a process in which a user enters contract content in natural language via a terminal, and the input content is analyzed by a server and generated as a draft contract.

[1339] A natural language description of what the program does

[1340] 1. User Input

[1341] The user enters the contract details in natural language into the input field on the terminal. For example, they enter something like "Company A will supply products to Company B every month, and Company B will pay for them."

[1342] 2. Receiving input

[1343] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using a secure communication protocol such as HTTPS.

[1344] 3. Natural Language Analysis

[1345] The server passes the received contract content in natural language to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, products, payment terms).

[1346] 4. Generate a draft

[1347] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and generates a draft contract by embedding the extracted requirements into the template. For example, a draft contract may be generated stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[1348] 5. Viewing Drafts

[1349] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[1350] 6. Receiving and Regenerating Modifications

[1351] If the user makes any changes to the draft, the changes are sent back to the server, which receives the changes and generates a new draft. This process is repeated until the user is satisfied.

[1352] 7. Save the Final Draft

[1353] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[1354] Specific examples

[1355] User Input

[1356] "Company A supplies goods to Company B every month, and Company B pays for them."

[1357] Server analysis results

[1358] Parties: Company A (supplier), Company B (recipient)

[1359] Product: Any product

[1360] Supply frequency: monthly

[1361] Payment terms: Payment within one month after delivery of goods

[1362] Generated contract draft

[1363] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1364] Article 1 (Supply of Goods)

[1365] The supplier shall provide a monthly supply of any good quality product.

[1366] Article 2 (Payment Terms)

[1367] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1368] Article 3 (Cancellation and Penalty Fees)

[1369] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1370] Comply with legal matters.

[1371] In this way, the system of the present invention automatically analyzes contract content entered by the user in natural language and generates a legally valid contract draft, enabling efficient and accurate contract drafting even for those without legal knowledge.

[1372] The processing flow will be explained below.

[1373] Step 1: The user enters the contract details into the terminal in natural language.

[1374] The user enters the contract details in natural language into the input field on the terminal. For example, "Company A will supply products to Company B every month, and Company B will pay for them."

[1375] Step 2: The device sends the input to the server

[1376] The terminal transmits the contract contents entered by the user in natural language to the server using a secure communication protocol (e.g., HTTPS).

[1377] Step 3: The server passes the input to the natural language processing engine

[1378] The server passes the received contract content in natural language to a natural language processing engine (NLP engine), which performs grammatical and semantic analysis.

[1379] Step 4: Natural language processing engine extracts requirements

[1380] The natural language processing engine extracts the necessary requirements for the contract (e.g., parties, products, payment terms). For example, it extracts "Company A: supplier, Company B: recipient, products: supplied monthly, payment terms: payment within one month after supply."

[1381] Step 5: The server selects a contract template

[1382] The server selects an appropriate contract template from among pre-prepared templates based on the extracted requirements.

[1383] Step 6: The server generates a draft contract

[1384] The server embeds the extracted requirements into the selected template and generates a draft contract, such as "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[1385] Step 7: The server sends the generated draft to the device

[1386] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[1387] Step 8: User reviews the draft and makes any necessary revisions

[1388] The terminal displays the received draft and the user checks it. If the user deems it necessary, they can make corrections to the draft, such as amending the payment terms.

[1389] Step 9: The device sends the modifications to the server

[1390] If the user modifies the draft, the device sends the modifications back to the server.

[1391] Step 10: The server regenerates the draft based on the modifications

[1392] The server regenerates a draft contract based on the received amendments, and the regenerated draft is sent to the terminal again.

[1393] Step 11: Review and save the final document

[1394] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[1395] Example 1

[1396] 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."

[1397] Conventional contract creation requires legal knowledge and is time-consuming and labor-intensive. Furthermore, manual contract creation is prone to human error, posing a risk of reducing the accuracy of the contract. Furthermore, revisions and version control are cumbersome, making it difficult to smoothly share contracts with the parties involved. To solve these problems, there is a need for a system that can automatically generate contracts and easily perform revisions and version control.

[1398] 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.

[1399] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content, performing grammatical and semantic analysis, and extracting necessary requirements for a contract, and means for selecting a contract template prepared in advance based on the extracted requirements and generating a contract draft. This makes it possible to automatically generate a contract efficiently and accurately based on the content entered by a user in natural language.

[1400] "User" refers to the entity that uses the system to input and confirm contract documents.

[1401] "Natural language" refers to a language used by humans on a daily basis, not a formal programming language or code.

[1402] "Receiving" is the process of taking information entered by a user and making it available within the system.

[1403] "Grammar analysis" is the process of analyzing the sentence structure of a natural language and identifying the part of speech and role of each word.

[1404] "Semantic analysis" is the process of understanding the meaning of words and phrases identified by grammatical analysis and grasping the meaning of the entire sentence.

[1405] "Contract requirements" refers to the basic information and clauses required for a contract, such as the parties, subject matter of the contract, and payment terms.

[1406] A "template" is a model of a contract, a predetermined document format into which input requirements are embedded.

[1407] A "Draft" is a generated, unfinalized, temporary document of a contract, subject to user review and amendment.

[1408] "Secure" refers to a state in which something is safe and protected from unauthorized access or data tampering.

[1409] "Version control" refers to a system that stores the change history of each version of a contract and allows for comparison and restoration between different versions.

[1410] A "natural language processing engine" is a collection of software and hardware for understanding and analyzing natural language, and performs grammatical analysis, semantic analysis, etc.

[1411] The present invention relates to a system that automatically generates a draft of a contract based on content entered by a user in natural language, and supports the creation of legally valid contracts. Specific embodiments for implementing this system are described below.

[1412] The user enters the contract details in natural language through the device. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them" into a form on the browser. The device then sends the entered details to the server using a secure communication protocol such as HTTPS.

[1413] After receiving the input, the server performs grammatical and semantic analysis using a natural language processing engine (e.g., Google Cloud Natural Language API or IBM Watson Natural Language Understanding), which extracts the necessary requirements for the contract (e.g., parties, products, and payment terms).

[1414] Next, the server selects an appropriate contract template from among those prepared in advance based on the analysis results and embeds the extracted requirements into the template. For example, it generates a contract draft stating, "Supplier A will supply goods to Recipient B every month, and Recipient B will pay Supplier A for the goods."

[1415] The generated draft is sent from the server to the device, which displays it to the user. The user reviews the draft and makes any necessary corrections. The corrected content is then sent back from the device to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[1416] The finalized draft of the contract is securely stored on the server, which uses a database (e.g., MySQL or PostgreSQL) to manage contract versions and also provides functionality to easily share and download contracts.

[1417] For example, if a user enters "Company A will supply goods to Company B every month, and Company B will pay for them" into a browser form and clicks the submit button, the following draft will be generated:

[1418] User Input

[1419] "Company A supplies goods to Company B every month, and Company B pays for them."

[1420] Server analysis results

[1421] Parties: Supplier (Company A), Recipient (Company B)

[1422] Product: Any product

[1423] Supply frequency: monthly

[1424] Payment terms: Payment within one month after delivery of goods

[1425] Generated contract draft

[1426] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1427] Article 1 (Supply of Goods)

[1428] The supplier shall provide a monthly supply of any good quality product.

[1429] Article 2 (Payment Terms)

[1430] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1431] Article 3 (Cancellation and Penalty Fees)

[1432] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1433] Comply with legal matters.

[1434] This system makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[1435] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1436] Step 1: User Input

[1437] The user enters the contract details in natural language into the input field on the device. Specifically, the user enters the following into a form on the browser: "Company A will supply products to Company B every month, and Company B will pay for them." The input data is saved in text format on the device.

[1438] Input: User inputs contract details in natural language

[1439] Output: Save natural language text data to your device

[1440] Step 2: Receiving input

[1441] The terminal receives the contract details entered by the user in natural language and sends them to the server using a secure communication protocol such as HTTPS. Specifically, JavaScript is used to send the input data to the server via an HTTP POST request.

[1442] Input: User's natural language text data

[1443] Output: Text data sent to the server

[1444] Step 3: Natural Language Analysis

[1445] The server passes the received contract content in natural language to a natural language processing engine (such as Google Cloud Natural Language API or IBM Watson Natural Language Understanding) for grammatical and semantic analysis. Specifically, the analysis engine analyzes the contract content and extracts the requirements necessary for the contract (parties, products, payment terms).

[1446] Input: Natural language text data received by the server

[1447] Output: Extraction results of requirements required for the contract (data in JSON format)

[1448] Step 4: Generate a draft

[1449] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. Specifically, it uses a Python script to run a template engine (e.g., Jinja2) and embeds the contract contents.

[1450] Input: Extraction results of requirements required for the contract

[1451] Output: Generated contract draft (text format)

[1452] Step 5: View the draft

[1453] The generated draft is sent from the server to the device, which then displays it to the user. Specifically, the draft is formatted using HTML and CSS and displayed in the browser. The user can view the displayed draft and perform operations such as scrolling and copy and paste.

[1454] Input: Generated contract draft

[1455] Output: A draft contract displayed in a browser

[1456] Step 6: Receive and regenerate corrections

[1457] If the user makes any changes to the draft, the changes are sent back to the server. Specifically, the device uses JavaScript to collect the changes and sends them back to the server as an HTTP POST request. The server receives the changes and generates a new draft.

[1458] Input: User modifications

[1459] Output: Regenerated draft with corrections

[1460] Step 7: Save the final draft

[1461] The final draft of the contract finalized by the user is stored securely on the server. The server uses a database (e.g., MySQL, PostgreSQL) to manage contract versions. It also provides functionality that makes it easy to share and download contracts. When the user clicks the download link, a PDF version of the contract is generated.

[1462] Input: Finalized contract draft

[1463] Output: Contract saved in database and PDF download link

[1464] (Application example 1)

[1465] 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."

[1466] Conventional contract drafting requires advanced legal knowledge and effort, and is even more difficult when it comes to specialized content such as contracts for the supply of factory robots. This situation hinders the efficient and accurate drafting of contracts and slows down business processes. The present invention aims to solve these problems and provide a method for easily drafting contracts in natural language.

[1467] 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.

[1468] In this invention, the server includes: means for receiving content entered by a user in natural language; means for analyzing the received natural language content and extracting contract requirements; means for generating a draft contract based on the extracted requirements; means for displaying the generated draft to the user; means for receiving content revised by the user again and generating a final contract draft; means for receiving content entered in natural language from a smartphone and transmitting the data to the server; means for analyzing the contract content, extracting requirements, and generating a draft contract by embedding them in a pre-prepared template; means for transmitting the generated draft from the server to the smartphone and displaying it to the user; means for transmitting content revised by the user again to the server and regenerating the contract reflecting the revisions; means for saving the finalized draft contract on the server; and means for generating a draft contract including information on the supplier and recipient, supply items, and payment terms. This enables efficient and accurate automatic generation of contracts regardless of legal knowledge or skills.

[1469] "User" means a person or company that uses the system to create a contract.

[1470] "Natural language" refers to a language used by humans on a daily basis, not a specialized programming language.

[1471] A "smartphone" is a type of mobile phone that can connect to the Internet and run applications.

[1472] A "server" is a computer system that provides services to clients over a network.

[1473] A "draft contract" is an early version of a document describing the contents of a contract, and is a preliminary document before becoming a final contract.

[1474] A "natural language processing engine" is a computer program that analyzes and understands the meaning of natural language used by humans.

[1475] "Requirements" refer to the essential items or clauses that must be included in the contract.

[1476] A "template" is a document with a predetermined format or structure for generating a draft contract.

[1477] "Supplier" refers to the party that supplies goods or services.

[1478] "Recipient" means the party receiving goods or services.

[1479] "Supplied Items" means goods or services provided by a Supplier to a Recipient.

[1480] "Payment terms" refers to the amount to be paid for the supplied items, the payment deadline, payment method, and other terms.

[1481] The present invention relates to a system that allows users to input contract details in natural language using a smartphone and automatically generates a draft contract based on that content. The contract details entered by the user via the smartphone are sent to a server, where they are analyzed by a natural language processing engine. A draft contract is then generated based on the analysis results and displayed to the user. A specific implementation method for this system is described below.

[1482] First, the user enters the contract details in natural language through a dedicated smartphone app. For example, the details might be something like, "The supplier will supply parts to the recipient every month, and the recipient will pay for them." The app then sends this information to the server. Secure communication protocols such as HTTPS are used for safe data transfer.

[1483] The server then passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis. Natural language processing engines such as spaCy and BERT can be used. This analysis extracts the necessary contract terms (parties, products / services, payment terms, etc.).

[1484] Next, based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. This automatically generates a draft contract. For example, the generated draft may look like the one below.

[1485] This Agreement is between the Supplier (hereinafter referred to as the "Supplier") and the Recipient (hereinafter referred to as the "Recipient"). The Supplier will supply parts (hereinafter referred to as the "Parts") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for the Parts.

[1486] The generated draft is sent from the server to the smartphone and displayed to the user. The user checks the displayed draft and makes corrections as necessary. If corrections are made, the content is sent again to the server, which receives the corrections and generates a new draft. This process is repeated until the user is satisfied.

[1487] The finalized draft of the contract is securely stored on the server. A database system is used for this storage. The saved draft of the contract can be easily referenced and updated in the future. It is also possible to manage versions of the contract and share it with the relevant parties.

[1488] Examples:

[1489] User Input: "The supplier will supply the parts to the recipient every month and the recipient will pay for them."

[1490] Example prompt sentence:

[1491] Factory C supplies fuel in engine terminals to Factory D every day, and Factory D pays for it.

[1492] By inputting these specific examples and prompt sentences, a draft contract is automatically generated, allowing for the efficient creation of legally valid contracts. This system makes it possible to create accurate contracts even without specialized knowledge.

[1493] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1494] Step 1: The user launches the smartphone app and enters the contract details in natural language.

[1495] The user launches the smartphone application and enters the contract details in a designated input field in natural language. For example, the user might enter, "The supplier will supply parts to the recipient every month, and the recipient will pay for them."

[1496] (Input) Contract details in natural language

[1497] (Output) Confirming user input on a smartphone

[1498] Step 2: The smartphone receives the user's input and sends it to the server.

[1499] The terminal receives the contract details entered by the user in natural language and transmits the data to the server, using the HTTPS protocol for secure data transfer.

[1500] (Input) The contract contents entered by the user in natural language

[1501] (Output) Secure data transmission to the server

[1502] Step 3: The server passes the received contract content in natural language to a natural language processing engine, which performs grammatical and semantic analysis.

[1503] The server passes the received natural language contract content to a natural language processing engine (e.g., spaCy, BERT), which performs grammatical and semantic analysis to extract the necessary contract terms (parties, products / services, payment terms).

[1504] (Input) Contract details in natural language

[1505] (Output) Extraction of contract requirements (e.g., supplier, recipient, supply items, payment terms)

[1506] Step 4: Based on the analysis results, the server selects an appropriate contract template from among the pre-prepared ones, embeds the requirements into the template, and generates a draft contract.

[1507] The server selects a contract template based on the extracted requirements and generates a draft contract by embedding the requirements in the template.

[1508] (Input) Contract requirements based on analysis results

[1509] (Output) Draft contract

[1510] Step 5: The server sends the generated draft to the smartphone and displays it to the user.

[1511] The server sends the generated draft of the contract to the smartphone, which displays it to the user, who can then review the draft and make any necessary corrections.

[1512] (Input) Draft contract

[1513] (Output) Display of drafts that users can see

[1514] Step 6: The user makes revisions to the draft and submits it to the server again.

[1515] The user makes corrections to the displayed draft and sends the corrections back to the server. The terminal receives the corrections and sends them back to the server.

[1516] (Input) User-modified contract details

[1517] (Output) Sending the modified data to the server

[1518] Step 7: The server receives the modifications and generates the draft again.

[1519] The server receives the amendments, analyzes them again using a natural language processing engine, and creates a re-drafted contract. This process is repeated until the user is satisfied.

[1520] (Input) User-modified contract details

[1521] (Output) Regenerated draft agreement

[1522] Step 8: The server saves the finalized draft of the contract.

[1523] The finalized draft of the contract is securely stored in a database system on the server, making it easy to refer to and update in the future. It also allows for version control of the contract and sharing with the relevant parties.

[1524] (Input) Finalized draft of contract

[1525] (Output) Save the draft to the server

[1526] 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.

[1527] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. An embodiment of the present invention includes a process for analyzing the user's input, extracting contract requirements, and reflecting the user's emotional data in the generated contract draft. The system of the present invention incorporates an emotion engine in addition to a natural language processing engine, and has the ability to recognize the user's emotions and appropriately adjust the content of the contract.

[1528] A natural language description of what the program does

[1529] 1. Obtaining user input and emotion data

[1530] The user enters the contract details in natural language into the input field on the device. At the same time, the device acquires emotional data from the user's input. For example, "Company A will supply products to Company B every month, and Company B will pay for them," and also acquires emotional data such as the user's stress level and joy.

[1531] 2. Sending input and emotional data

[1532] The terminal transmits the contract details entered by the user in natural language and the acquired emotion data to the server using a secure communication protocol (e.g., HTTPS).

[1533] 3. Natural Language Analysis

[1534] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[1535] 4. Emotion Data Analysis

[1536] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[1537] 5. Draft generation and adjustment

[1538] Based on the analysis results, the server selects an appropriate contract template from pre-prepared ones and embeds the extracted requirements into the template. It also adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adjusts the content of the contract to be concise and clear.

[1539] 6. Viewing Drafts

[1540] The generated draft is sent from the server to the terminal, which displays it to the user, who can then review the displayed draft and make corrections as necessary.

[1541] 7. Receiving and Regenerating Modifications

[1542] If the user makes any changes to the draft, the changes are sent back to the server, which then receives the changes, adjusts them based on the emotion data, and generates a new draft. This process is repeated until the user is satisfied.

[1543] 8. Save the Final Draft

[1544] The finalized draft of the contract is securely stored on the server, making it easy to refer to and update in the future. For example, it allows for version control of the contract and sharing with stakeholders.

[1545] Specific examples

[1546] User Input and Emotional Data

[1547] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[1548] Emotional data: High stress levels

[1549] Server analysis results

[1550] Parties: Company A (supplier), Company B (recipient)

[1551] Product: Any product

[1552] Supply frequency: monthly

[1553] Payment terms: Payment within one month after delivery of goods

[1554] Emotional state: Stress

[1555] Generated contract draft

[1556] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1557] Article 1 (Supply of Goods)

[1558] The supplier shall provide a monthly supply of any good quality product.

[1559] Article 2 (Payment Terms)

[1560] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1561] Article 3 (Cancellation and Penalty Fees)

[1562] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1563] Comply with legal matters.

[1564] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[1565] The processing flow will be explained below.

[1566] Step 1: The user enters the contract details into the terminal in natural language.

[1567] The user enters the contract details in natural language into the device's input field. For example, "Company A will supply products to Company B every month, and Company B will pay for them." The device also obtains the user's emotional data from this input.

[1568] Step 2: The device sends the input and emotion data to the server.

[1569] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS).

[1570] Step 3: The server parses the natural language content

[1571] The server passes the received natural language content to a natural language processing engine (NLP engine) for grammatical and semantic analysis, which extracts the necessary requirements for the contract (e.g., parties, supply items, payment terms).

[1572] Step 4: The server analyzes the emotion data

[1573] The server passes the received emotion data to the emotion engine, which analyzes the user's emotional state, for example, determining whether the user is feeling stressed.

[1574] Step 5: The server generates a draft contract

[1575] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. At the same time, the server adjusts the content and wording of the draft contract based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[1576] Step 6: The server sends the generated draft to the device

[1577] The server sends the generated draft contract to the device, again using a secure communication protocol (e.g., HTTPS).

[1578] Step 7: The device displays the draft, and the user can review and edit it.

[1579] The terminal displays the received draft to the user, who then checks the displayed draft and makes any necessary corrections, such as "change payment terms."

[1580] Step 8: The device sends the modifications to the server

[1581] If the user modifies the draft, the device sends the modifications to the server.

[1582] Step 9: The server regenerates the draft based on the modifications

[1583] The server re-generates a draft contract based on the received revisions. At this time, the emotional state is re-analyzed using the emotion engine, and an adjusted draft is re-generated. The re-generated draft is then sent back to the terminal.

[1584] Step 10: Review and save the final draft

[1585] Once the user is satisfied with the final draft, the server securely stores the final contract draft in a database for easy future reference and updates.

[1586] Through each of the above processing steps, the system of the present invention efficiently creates and amends a legally valid contract draft based on the contract content and emotion data entered by the user in natural language, and safely stores the final contract.

[1587] Example 2

[1588] 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."

[1589] Conventional contract drafting systems require advanced legal knowledge to accurately analyze contract content entered by users in natural language and generate appropriate contract drafts. Furthermore, they are unable to take the user's emotional state into account, resulting in poor usability. In particular, when users draft contracts while feeling stressed or anxious, their emotions can affect the content of the contract, resulting in the risk of an inaccurate contract being generated. This makes it difficult to efficiently draft legally valid and user-friendly contracts.

[1590] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1591] In this invention, the server includes means for receiving content entered by a user in natural language, means for analyzing the received natural language content and extracting contract requirements, means for acquiring emotion data, means for generating a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content revised by the user again and generating a final contract draft, and means for saving the final contract draft. This makes it possible to generate a contract draft that is accurate, legally valid, and adjusted to take the user's emotions into consideration, based on the user's natural language input content and emotion data.

[1592] A "user" is a person who provides natural language input to interact with the system and generate a draft contract.

[1593] "Natural language" refers to a language that humans use on a daily basis, and includes text data that has grammar and meaning.

[1594] "Emotional data" refers to data about a user's emotional state obtained when the user provides input, and includes emotional information such as stress level and joy.

[1595] A "natural language processing engine" is software that analyzes natural language text, understands its grammar and meaning, and converts it into structured data.

[1596] An "emotion engine" is software that analyzes emotional data and identifies the user's emotional state.

[1597] A "draft contract" is a preliminary contract document generated based on user input and requirements extracted by the system.

[1598] A "server" is a computer system that receives and processes data sent by a user from a terminal.

[1599] A "terminal" is an electronic device used by a user to provide input.

[1600] "Generate" refers to the system creating new data or documents based on input data.

[1601] "Preserving" refers to keeping generated data and documents available for a long period of time.

[1602] The present invention relates to a system that automatically generates a draft contract based on content entered by a user in natural language, supporting the creation of legally valid contracts. This system includes a process that analyzes the user's input, extracts contract requirements, and reflects the user's emotional data in the generated contract draft.

[1603] The system of the present invention comprises the following elements:

[1604] 1. Obtaining user input and emotion data

[1605] The user enters the contract details in natural language into the device's input field. The device simultaneously acquires the user's emotional data (stress level, joy, etc.). To acquire the emotional data, the device uses the device's built-in camera and microphone to analyze facial expressions and tone of voice.

[1606] 2. Sending input and emotional data

[1607] The terminal transmits the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, the transmitted data may contain the following format: "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[1608] 3. Natural Language Analysis

[1609] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API), which performs grammatical and semantic analysis to extract the necessary requirements for the contract (parties, supply items, payment terms). For example, elements such as "Company A (supplier), Company B (recipient), monthly, payment terms" can be extracted from the input content.

[1610] 4. Emotion Data Analysis

[1611] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[1612] 5. Draft generation and adjustment

[1613] The server selects an appropriate contract template (e.g., a DocuSign template) from among pre-prepared templates based on the analysis results obtained from the natural language processing engine and emotion engine. It then incorporates the extracted requirements into the template and adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[1614] 6. Viewing Drafts

[1615] The generated contract draft is sent from the server to the terminal, which then displays it to the user. The user can review the draft on the screen and, if any corrections are needed, enter the corrections directly into the text field.

[1616] 7. Receiving and Regenerating Modifications

[1617] If the user makes any edits to the draft, the device sends the edits back to the server, which receives the edits, reanalyzes the emotion data if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[1618] 8. Save the Final Draft

[1619] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[1620] Specific examples

[1621] User Input and Emotional Data

[1622] Example: "Company A supplies goods to Company B every month, and Company B pays for them."

[1623] Emotional data: High stress levels

[1624] Server analysis results

[1625] Parties: Company A (supplier), Company B (recipient)

[1626] Product: Any product

[1627] Supply frequency: monthly

[1628] Payment terms: Payment within one month after delivery of goods

[1629] Emotional state: Stress

[1630] Generated contract draft

[1631] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1632] Article 1 (Supply of Goods)

[1633] The supplier shall provide a monthly supply of any good quality product.

[1634] Article 2 (Payment Terms)

[1635] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1636] Article 3 (Cancellation and Penalty Fees)

[1637] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1638] Comply with legal matters.

[1639] In this way, the system of the present invention automatically analyzes the contract content entered by the user in natural language and further adjusts the contract draft based on emotional data, thereby enabling the creation of legally valid contracts that are easy for the user to use. This makes it possible to create contracts efficiently and accurately, even without legal knowledge.

[1640] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1641] Step 1:

[1642] Capturing user input and emotion data

[1643] The user enters the contract details in natural language into the device's input field. For example, the user might enter "Company A will supply products to Company B every month, and Company B will pay for them." At this time, the device uses its camera and microphone to simultaneously capture emotional data (stress level, joy, etc.) as the user types. For example, the device captures the entered text, as well as facial expression analysis data and tone of voice analysis data.

[1644] Input: Natural language contract content, emotional data

[1645] Output: Received natural language data and emotion data

[1646] Step 2:

[1647] Sending input and emotion data

[1648] The terminal sends the contract details entered by the user in natural language and the acquired emotional data to the server using a secure communication protocol (e.g., HTTPS). For example, data is sent in the form of "Contract details: Company A supplies products to Company B every month, Emotional data: Stress level high."

[1649] Input: Received natural language data, emotion data

[1650] Output: Natural language data and emotion data sent to the server

[1651] Step 3:

[1652] Natural Language Analysis

[1653] The server passes the received natural language content to a natural language processing engine (e.g., Google Cloud Natural Language API) for grammatical and semantic analysis, which extracts the necessary requirements for the contract. For example, the server extracts elements such as "Company A (supplier), Company B (receiver), monthly, payment terms" from the input content.

[1654] Input: Natural language data

[1655] Output: Extracted contract requirements data (parties, supply items, payment terms, etc.)

[1656] Step 4:

[1657] Emotional Data Analysis

[1658] The server passes the received emotion data to an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotional state. For example, if the user is feeling stressed while typing, the emotion engine will return an analysis result such as "high stress level" to the server.

[1659] Input: Emotion data

[1660] Output: Emotion analysis result data (e.g., high stress level)

[1661] Step 5:

[1662] Draft generation and adjustment

[1663] The server uses the analysis results from the natural language processing engine and emotion engine to select an appropriate contract template (e.g., a DocuSign template) from among the pre-prepared templates, and incorporates the extracted requirements into the template. Furthermore, the server adjusts the content and wording of the draft based on the emotion data. For example, if the user is feeling stressed, the server adjusts the contract text to be more concise and clear.

[1664] Input: Extracted contract requirements data, sentiment analysis result data

[1665] Output: Adjusted draft contract

[1666] Step 6:

[1667] View Drafts

[1668] The generated contract draft is sent from the server to the terminal, which displays the draft to the user, who can then check the draft on the screen. For example, the user can check the contract contents and identify any necessary revisions.

[1669] Input: Adjusted contract draft

[1670] Output: A draft of the contract displayed on the device

[1671] Step 7:

[1672] Receive and regenerate corrections

[1673] If the user makes any changes to the draft, the device sends the changes back to the server, which receives the changes, re-analyzes them if necessary, and regenerates the draft. This process is repeated until the user is satisfied.

[1674] Input: User modifications

[1675] Output: Final regenerated contract draft

[1676] Step 8:

[1677] Save the final draft

[1678] Once the user has finally reviewed and approved the contract draft, it is securely stored on the server. The server manages multiple versions of the draft and can share them with relevant parties as needed. The saved format can be selected from PDF, XML, etc., and is encrypted for security purposes.

[1679] Input: Final contract draft

[1680] Output: A draft contract saved on the server

[1681] The above is the flow of processing in the system of the present invention.

[1682] (Application example 2)

[1683] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1684] Conventional contract creation systems simply reflected the content entered by the user in natural language, and the quality of the final contract was often affected by the user's emotional state and the accuracy of the input. This led to issues with inconsistent quality of the final contract. In particular, when users were stressed or tired, input errors and unclear expressions increased, which could cause contract issues. Furthermore, the lack of a user-friendly interface for instantly entering and adjusting contract content on-site made it difficult to operate in factories and other workplaces.

[1685] 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.

[1686] In this invention, the server includes means for receiving content input in natural language by a user, means for analyzing the received natural language content and extracting contract requirements, means for generating and adjusting a draft contract based on the extracted requirements and emotion data, means for displaying the generated draft to the user, means for receiving content modified by the user again and generating a final contract draft, means for saving the final contract draft, means for acquiring the input content and emotion data via smart glasses or a head-mounted display used for generating and adjusting the contract draft, and means for using a secure communication protocol to transmit data to a remote server. This enables the generation of an optimal contract draft according to the user's emotional state, enabling rapid and high-quality contract creation on the factory floor.

[1687] "User" means a person who uses the system to create or modify a contract.

[1688] "Natural language" refers to a language that humans use on a daily basis and is used to input contract details.

[1689] "Emotional data" is data that expresses a user's emotional state in numerical or categorical terms, including stress levels, joy, etc.

[1690] "Contract requirements" are the basic information and clauses that should be included in the contract, such as the parties, items to be supplied, and payment terms.

[1691] A "draft" is a preliminary agreement prepared before the final agreement.

[1692] "Smart glasses" are glasses-type wearable devices equipped with a display and sensors and capable of displaying information using AR technology.

[1693] A "head-mounted display (HMD)" is a display device worn on the head that directly displays visual information.

[1694] A "secure communication protocol" is a communication protocol for securely sending and receiving data, and includes HTTPS.

[1695] A "natural language processing engine (NLP engine)" is a software module for analyzing natural language and understanding its meaning.

[1696] An "emotion analysis engine" is a software module that analyzes a user's emotional data and determines their emotional state.

[1697] A "remote server" is a server device that contains computer resources and data at a remote location that can be accessed via a network.

[1698] "Contract disputes" refer to disputes or problems between the parties that arise due to misunderstandings or non-performance of the contractual terms.

[1699] "Factory floor" refers to the physical facility or location where goods are manufactured or production activities take place.

[1700] A system embodying the present invention includes the following elements for quickly and accurately creating contracts on the factory floor:

[1701] Hardware and Software

[1702] Hardware: Smart glasses or head-mounted displays (HMDs) act as interfaces to receive user input. These devices are used by users to enter contract details. Additionally, these devices monitor and collect data on the user's emotional state.

[1703] Software: Natural language processing engine (NLP engine) and sentiment analysis engine. These engines run on the server and analyze the natural language and sentiment data entered by the user.

[1704] Program processing

[1705] 1. Obtaining user input and emotion data

[1706] The user inputs the contract details in natural language via smart glasses or an HMD, while the device simultaneously captures the user's emotional data (e.g., stress level and happiness).

[1707] 2. Sending input and emotional data

[1708] The contract details entered by the user in natural language and the acquired emotional data are sent to the server using a secure communication protocol (HTTPS).

[1709] 3. Server Analysis

[1710] The server passes the received natural language content to a natural language processing engine for grammatical and semantic analysis, which extracts the necessary requirements for the contract (parties, supply items, payment terms).

[1711] The server then passes the received emotional data to an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the server analyzes the data.

[1712] 4. Contract draft generation and adjustment

[1713] Based on the analysis results, the server selects an appropriate contract template from among those prepared in advance and embeds the extracted requirements into the template. It also adjusts the content and wording of the contract based on the results of the sentiment analysis. For example, if the user is feeling stressed, the contract content will be adjusted to be concise and clear.

[1714] 5. View and edit drafts

[1715] The generated contract draft is sent from the server to the device and displayed to the user through smart glasses or an HMD, where the user can review the displayed draft and make any necessary corrections.

[1716] Specific examples

[1717] Example user input: "Company A supplies goods to Company B every month, and Company B pays for them."

[1718] Emotional data: User's stress level is high

[1719] Server analysis results

[1720] Parties: Company A (supplier), Company B (recipient)

[1721] Product: Any product

[1722] Supply frequency: monthly

[1723] Payment terms: Payment within one month after delivery of goods

[1724] Emotional state: User is under high stress

[1725] Generated Agreement Draft:

[1726] This contract is between Supplier A (hereinafter referred to as "Supplier") and Recipient B (hereinafter referred to as "Recipient"). The Supplier will supply products (hereinafter referred to as "Products") to the Recipient on a monthly basis, and the Recipient will pay the Supplier for them.

[1727] Article 1 (Supply of Goods)

[1728] The supplier shall provide a monthly supply of high quality concise goods.

[1729] Article 2 (Payment Terms)

[1730] The recipient shall transfer the payment to the account designated by the supplier by the end of the month following the date on which the supplier supplies the goods.

[1731] Article 3 (Cancellation and Penalty Fees)

[1732] If either the Supplier or the Recipient breaches this Agreement, the other party shall have the right to terminate this Agreement and the breaching party shall pay a penalty.

[1733] Comply with legal matters.

[1734] Example prompt for a generative AI model:

[1735] "Company A will supply products to Company B every month, and Company B will pay for them. This is causing users a lot of stress. Please write the contract succinctly and clearly, and automatically generate a draft."

[1736] In this way, by using this system, users can generate optimal contract drafts according to their emotional state, enabling fast and high-quality contract creation on the factory floor.

[1737] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1738] Step 1:

[1739] The user inputs the contract details in natural language via smart glasses or a head-mounted display. The input data includes the contract details text and emotional data. The emotional data includes the user's stress level and happiness. As a result, the device acquires the contract details and emotional data.

[1740] Step 2:

[1741] The device transmits the acquired natural language contract details and emotion data to the server using a secure communication protocol (HTTPS). This transmission process ensures that the data is delivered to the server safely. The input includes the user's contract details text and emotion data, and the output is the data sent to the server.

[1742] Step 3:

[1743] The server passes the received contract text to a natural language processing engine (NLP engine) for grammatical and semantic analysis. Specifically, it extracts the necessary contract requirements, such as the parties, supply items, and payment terms, from the input contract text. The input contains the contract text, and the extracted requirements are obtained as the output.

[1744] Step 4:

[1745] The server passes the received emotional data to the emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, the data is analyzed. The input contains emotional data, and the output is a result about the user's emotional state.

[1746] Step 5:

[1747] The server selects an appropriate contract template from pre-prepared ones based on the analyzed contract requirements and emotional data, and generates a contract draft. The content and wording of the contract are adjusted based on the results of the emotional analysis. For example, if the user is feeling stressed, the content of the contract is adjusted to be concise and clear. The input includes the extracted contract requirements and the results of the emotional state, and the adjusted contract draft is generated as the output.

[1748] Step 6:

[1749] The generated contract draft is sent from the server to the terminal via smart glasses or a head-mounted display and displayed to the user. The user can check the displayed draft and make any necessary corrections. The input includes the contract draft, and the output is the user's confirmation and corrections.

[1750] Step 7:

[1751] If the user modifies the draft contract, the modifications are sent from the device to the server again. The server receives the modifications, analyzes and adjusts them again, and generates the final draft. This process is repeated until the user is satisfied. The input contains the user's modifications, and the output is the final draft contract.

[1752] Step 8:

[1753] The finalized contract draft is securely stored on the server for easy future reference and updating. This allows contract version control and sharing with stakeholders. The input includes the final contract draft, and the output is secure storage of the contract.

[1754] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1755] 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.

[1756] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1757] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1758] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1759] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1760] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1761] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1762] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1763] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1764] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1765] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1766] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1767] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1768] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1769] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1770] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1771] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1772] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1773] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1774] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1775] The following is further disclosed regarding the above embodiment.

[1776] (Claim 1)

[1777] means for receiving natural language input from a user;

[1778] means for analyzing the received natural language content and extracting requirements of the contract;

[1779] means for generating a draft contract based on the extracted requirements;

[1780] means for displaying the generated draft to a user;

[1781] a means for receiving the user's amendments again and generating a final contract draft;

[1782] and means for storing said final contract draft.

[1783] (Claim 2)

[1784] 2. The system according to claim 1, wherein the natural language analysis is performed using a natural language processing engine.

[1785] (Claim 3)

[1786] 2. The system of claim 1, wherein the requirements of the contract include legal provisions.

[1787] "Example 1"

[1788] (Claim 1)

[1789] means for receiving natural language input from a user;

[1790] means for analyzing the content of the received natural language, performing grammatical analysis and semantic analysis, and extracting necessary requirements for the contract;

[1791] A means for selecting a contract template prepared in advance based on the extracted requirements and generating a contract draft;

[1792] means for displaying the generated draft to a user;

[1793] a means for receiving the content corrected by the user again, detecting the difference, and generating a new draft;

[1794] The system includes a means for securely storing and versioning the final contract draft.

[1795] (Claim 2)

[1796] 2. The system according to claim 1, wherein the natural language analysis is performed using a natural language processing engine.

[1797] (Claim 3)

[1798] 2. The system of claim 1, wherein the requirements of the contract include legal provisions.

[1799] "Application Example 1"

[1800] (Claim 1)

[1801] means for receiving natural language input from a user;

[1802] means for analyzing the received natural language content and extracting requirements of the contract;

[1803] means for generating a draft contract based on the extracted requirements;

[1804] means for displaying the generated draft to a user;

[1805] a means for receiving the user's amendments again and generating a final contract draft;

[1806] means for storing said final contract draft;

[1807] A means for receiving content input in natural language from a smartphone and transmitting the data to a server;

[1808] A method for generating a draft contract by analyzing the contract contents, extracting requirements, and embedding them in a pre-prepared template.

[1809] A means for transmitting the generated draft from the server to a smartphone and displaying it to the user;

[1810] A means for the user to resubmit the revised draft to the server and regenerate it reflecting the revised content;

[1811] A means of storing the finalized draft of the contract on the server;

[1812] A system including means for generating a draft contract including information about the supplier and recipient, items to be supplied, and payment terms.

[1813] (Claim 2)

[1814] 2. The system according to claim 1, wherein the natural language analysis is performed using a natural language processing engine.

[1815] (Claim 3)

[1816] 2. The system of claim 1, wherein the requirements of the contract include legal provisions.

[1817] "Example 2: Combining Emotion Engines"

[1818] (Claim 1)

[1819] means for receiving natural language input from a user;

[1820] means for analyzing the received natural language content and extracting contract requirements;

[1821] A means for acquiring emotion data;

[1822] means for generating a draft contract based on the extracted requirements and emotion data;

[1823] means for displaying the generated draft to a user;

[1824] a means for receiving the user's amendments again and generating a final contract draft;

[1825] and means for storing said final contract draft.

[1826] (Claim 2)

[1827] 2. The system according to claim 1, wherein the natural language analysis is performed using a natural language processing engine.

[1828] (Claim 3)

[1829] 10. The system of claim 1, wherein the contractual requirements include legal provisions.

[1830] (Claim 4)

[1831] 10. The system of claim 1, wherein the emotion data uses an emotion engine to analyze the user's emotional state.

[1832] (Claim 5)

[1833] 2. The system according to claim 1, wherein the content of the generated contract draft is adjusted based on the emotion data.

[1834] "Application example 2 when combining emotion engines"

[1835] (Claim 1)

[1836] means for receiving natural language input from a user;

[1837] means for analyzing the received natural language content and extracting requirements of the contract;

[1838] means for generating and adjusting a draft contract based on the extracted requirements and sentiment data;

[1839] means for displaying the generated draft to a user;

[1840] a means for receiving the user's amendments again and generating a final contract draft;

[1841] a means for storing said final draft agreement;

[1842] means for acquiring input and emotion data via smart glasses or a head-mounted display used for generating and adjusting the contract draft;

[1843] Means for using a secure communication protocol to transmit data to a remote server

[1844] A system including:

[1845] (Claim 2)

[1846] 2. The system according to claim 1, wherein the natural language analysis is performed using a natural language processing engine.

[1847] (Claim 3)

[1848] 2. The system of claim 1, wherein the requirements of the contract include legal provisions. [Explanation of symbols]

[1849] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving natural language input from a user; means for analyzing the received natural language content and extracting requirements of the contract; means for generating a draft contract based on the extracted requirements; means for displaying the generated draft to a user; a means for receiving the user's amendments again and generating a final contract draft; and means for storing said final contract draft.

2. 2. The system according to claim 1, wherein the natural language analysis is performed using a natural language processing engine.

3. 2. The system of claim 1, wherein the contract requirements include legal provisions.

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