system

Abstract

Provide a system. 【Solution means】 Means for receiving an aggregate of legal-related information, Means for electronically converting the received information and transferring it to a remote device, Means for analyzing legal-related information by utilizing a legal information infrastructure and current regulatory information, Means for identifying legal risk items and evaluating the corresponding items, Means for making legal jargon in an intuitively understandable form and constructing an optimal amendment, Means for presenting the generated amendment to the user and aggregating opinions, Means for finally generating and supplying the legally amended information, Means for interpreting contract information in international transactions in real time and promoting legal compliance, A system including the above.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, appropriate evaluation and risk management of legal documents and contracts have been required. However, many companies and individuals face their complexity and find it difficult to respond efficiently and accurately. Especially in a multinational environment, analyzing legal documents while considering multiple languages and differences in different legal systems requires high expertise and a great deal of labor, which places a heavy burden on users. In addition, due to frequent law revisions, there is a problem that it is difficult to conduct legal checks that always reflect the latest information.

Means for Solving the Problems

[0005] The present invention provides a system that includes means for inputting legal documents, means for converting the input legal documents into digital data and transmitting them to a server, means for analyzing legal documents by referring to a legal database and the latest legal amendment information, means for extracting risky clauses and evaluating those clauses, means for simplifying legal terminology and generating appropriate alternatives, means for presenting the generated alternatives to the user and receiving feedback, and means for generating and providing the final revised legal document. By providing this system, the present invention streamlines the analysis of legal documents, provides an environment that enables analysis in multiple languages, and allows users to easily mitigate legal risks.

[0006] A "legal document" is a document that has legal effect, and includes documents that contain matters related to the law, such as contracts, agreements, and rulebooks.

[0007] "Converting to digital data" is the process of changing an analog or physical document into a format that can be processed by a computer.

[0008] A "server" is a computer system that provides data and services to other computers and terminals via a network.

[0009] A "legal database" is a collection of data in which information related to the law is systematically gathered and made easily searchable.

[0010] "Legal amendment information" refers to information regarding changes made to existing laws or newly enacted laws.

[0011] "Analysis" is the process of thoroughly examining data and information for a specific purpose to reveal its meaning and characteristics.

[0012] A "risk clause" is a clause included in a contract or document that could potentially cause legal problems or disputes in the future.

[0013] "Evaluation" is the process of judging the value, effectiveness, and impact of something based on specific criteria.

[0014] An "alternative" is another option or solution to the original proposed plan.

[0015] "Feedback" refers to reactions or opinions given in response to certain actions or data, and is information that is useful for subsequent improvements. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention provides an advanced system for users to analyze legal documents. This system allows for efficient processing of legal documents, from input to final revision. The user first uploads the legal document using a terminal. The terminal converts this document into digital data and sends it to the server.

[0038] The server analyzes documents by cross-referencing them with legal databases and the latest legal amendment information. During this analysis, it detects risky clauses and legal issues within the document. This includes ambiguous wording in contracts and clauses that do not meet international legal standards. The server then simplifies legal terminology and automatically generates user-friendly alternatives. In this way, the server quickly assesses the legal risks of contracts and agreements and presents them to the user.

[0039] Users can review alternative and revised proposals presented via their devices. For example, when a user analyzes an international contract between Japanese and American companies, the server identifies potential legal risks arising from differences between Japanese and American law and presents specific alternatives. In this way, users can revise the contract on the spot based on the presented revisions and send feedback to the server.

[0040] The server then receives feedback from the user, generates a final revised document, and presents it to the user again. The user can save or print this final version. Furthermore, the system supports multilingual legal documents and enables consistent analysis across different language environments. This allows users to ensure international compliance and enhance brand credibility.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user uploads a legal document using their device. The device receives this document and converts it into digital text data using OCR (Optical Character Recognition) technology. The converted data is then sent to the server.

[0044] Step 2:

[0045] The server receives text data and accesses legal databases and the latest legal amendment information. The server analyzes the document's content and detects risks in light of the law. This includes unclear terminology and potentially legally problematic clauses.

[0046] Step 3:

[0047] The server assesses the detected risks and generates alternatives and improvements as needed. The server rephrases legal terminology into a more understandable format and creates a proposal document. This information is provided to the user as a concrete example for accepting legal recommendations.

[0048] Step 4:

[0049] The terminal receives suggestions and alternatives from the server and presents them visually to the user. The user can then review contracts and legal documents based on this information and make necessary revisions. The user then inputs feedback on the revisions into the terminal.

[0050] Step 5:

[0051] The device that receives user feedback sends it to the server. The server generates the final revised legal document based on the feedback.

[0052] Step 6:

[0053] The server sends the final revised document to the terminal. The terminal presents the revised document to the user, who can then save or print it.

[0054] This series of processes allows users to perform legal checks on legal documents efficiently and accurately.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] Information analysis and evaluation are complex and time-consuming tasks, particularly in legal and technical fields, making it difficult for users to process documents efficiently and accurately. Furthermore, there is a growing need for information processing that supports multiple languages ​​while meeting international standards, but systems to meet these requirements are insufficient.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes a device for inputting information, a device for converting the input information into data and transmitting it, and a device for analyzing the information by referring to an information database and the latest update information. This enables users to efficiently analyze multilingual information and obtain appropriate alternatives, thereby enabling information processing that meets international standards.

[0060] A "device for inputting information" is a device that has the function of allowing users to provide data to be analyzed to a system using an application or web interface.

[0061] A "device that converts and transmits data" is a device that converts input information into a digital data format and sends it to a server for necessary analysis processes.

[0062] An "information database" is a collection of information used to verify information being analyzed, and is a digital resource that includes laws and technical data.

[0063] "Latest updates" refers to new information that has been changed or added, and in particular includes the latest data on laws and technologies.

[0064] An "analytical device" is a device that uses an information database and the latest updates to analyze input data and identify risks and other important items.

[0065] "Multilingual information" refers to information expressed in multiple languages ​​and includes data that can be adapted to international contexts.

[0066] An "appropriate alternative" is a proposal that improves upon the original information based on the information obtained through analysis and is presented in a way that is easy for users to understand.

[0067] "International standards" refer to common rules and guidelines across different countries and regions, and are the standards necessary for cross-border business and legal activities.

[0068] This invention provides an advanced system for inputting and analyzing information. The user uploads the information to be analyzed to the system using a terminal. The terminal converts this information into digital data and sends it to a server for analysis. The terminal can accurately extract data from paper and electronic media using text recognition and scanning technologies.

[0069] The server compares this digital data with legal and technical information databases, as well as the latest updates. During the analysis phase, natural language processing (NLP) techniques are used to identify risks and ambiguities within the input data. This allows for the rapid extraction of unclear areas and potential risks based on laws and technical standards.

[0070] Furthermore, the server uses a generative AI model to automatically generate appropriate alternatives for identified risks. This allows for the conversion of technical jargon into simpler language, presenting revised solutions in an easily understandable format for the user. Based on this information, the user can easily review the revised solutions on their device and send feedback back to the server. The server then generates the final information based on the user's feedback, presenting the most suitable content for the user.

[0071] This system supports information in multiple languages ​​and can perform analysis that conforms to international standards. This allows users to process information in a consistent process across different language environments, ensuring international compliance.

[0072] As a concrete example, the prompt text to be input to the generative AI model is as follows:

[0073] "Analyze the risk clauses in the international contract and propose alternatives that comply with the legal standards of the specific country / region."

[0074] This prompt allows the system to efficiently analyze various legal documents and enable necessary legal compliance.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The user uses a terminal to upload information that needs to be analyzed to the system. The input is provided as legal documents, such as PDF or Word files. The terminal utilizes text recognition technology to convert these documents into digital data. This converted digital data is then output and sent to the next process.

[0078] Step 2:

[0079] The server receives the converted digital data. The server then begins analyzing the input data using its information database and the latest updates. This process utilizes natural language processing (NLP) to identify risky elements and ambiguous expressions within the document. The output includes the identified risk elements and analysis results.

[0080] Step 3:

[0081] Based on the analysis results, the server uses a generative AI model to generate alternative solutions that are easy for the user to understand. Identified risk factors and ambiguous expressions are considered as input. The generative AI model then performs data calculations to generate alternative solutions, such as "modified solutions that conform to international standards." The output is a list of easily understandable modified solutions.

[0082] Step 4:

[0083] The user reviews the alternative and corrective suggestions provided by the server through their terminal. From the provided corrective suggestions, the user selects the necessary changes and performs the specific actions to send feedback to the server. The output is feedback data containing the correction instructions given by the user.

[0084] Step 5:

[0085] The server receives feedback from users and generates the final revised information. User feedback data is used as input. Based on this data, the server makes any further necessary adjustments to generate the completed legal document or information. The output is the final version of the document provided to the user.

[0086] Step 6:

[0087] The user uses a terminal to receive the final version of the information provided by the server and to perform operations to save or print it. The input is the completed document provided by the server. The output is the document saved by the user in the desired format (e.g., digital storage or print).

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] In an international legal environment, analyzing contracts and terms of service is complex, and implementing this analysis, including multilingual support, is difficult. In particular, cross-border electronic payment services require rapid and accurate assessment and response to legal risks. However, traditional methods are insufficient for analyzing such legal information and providing appropriate revisions, potentially leading to legal disputes and damage to brand credibility.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for receiving a collection of legal information, means for analyzing the legal information using a legal information infrastructure and current legal information, and means for identifying legal risk items and evaluating those items. This makes it possible to interpret contract information in international transactions in real time and promote legal compliance.

[0093] A "collection of legal information" refers to a data set that encompasses all legally related information, such as various legal documents, regulations, and contracts.

[0094] "Means of electronic conversion and transfer to remote devices" refers to the process of converting physical or non-electronic legal documents into digital data and transferring them to servers or external devices.

[0095] "Legal information infrastructure and current legal information" refers to a knowledge base that includes databases related to laws and the latest information on legal amendments.

[0096] A "legal risk item" is an element within a legal document that identifies potential legal problems or areas that could lead to future litigation.

[0097] "Intuitively understandable legal terminology" refers to a state where complex legal jargon is replaced with expressions that are easy for the average user to understand.

[0098] Interpreting "contractual information in international transactions" refers to the process of accurately understanding and evaluating information regarding contracts concluded between countries and regions with different legal backgrounds.

[0099] The system of this invention aims to process international contracts safely and efficiently by analyzing legal information and assessing legal risks. This system is implemented in a network environment including client devices and servers.

[0100] First, the user inputs a collection of legal information using a device such as a smartphone or computer. Once the user uploads legal documents to the device, the device uses OCR technology to convert these documents into digital data. OCR software such as Tesseract is used for this conversion.

[0101] The converted digital data is transmitted to a server via the internet. The server has a Python®-based analysis engine and a database for referencing legal information infrastructure and current legal information. It also analyzes legal documents using natural language processing (NLP) libraries (e.g., Spacy and BERT) to identify legal risk items.

[0102] For example, if a user uploads a transaction contract between a Japanese company and an overseas company, the server analyzes the differences based on the laws of the relevant countries. This identifies risky clauses and generates and presents alternatives to the user in an intuitively understandable format, avoiding legal jargon.

[0103] Examples of specific prompts include, "Analyze the following legal document, identify legal risks, and generate alternative solutions." Through this process, the system can perform real-time legal risk assessments and support secure international transactions.

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The user inputs a collection of legal information using a smartphone or computer. The input information is legal documents in physical or non-electronic form. The device converts these documents into digital data using optical character recognition (OCR) technology. In this step, data processing is performed using OCR software such as Tesseract, and the output is the conversion of image data into text data.

[0107] Step 2:

[0108] The terminal transmits the converted digital data to the server via the internet. The input here is a legal document transcribed into text by OCR, and the output to the server is the data transfer process. This prepares the document for further analysis.

[0109] Step 3:

[0110] The server analyzes the received digital data. The server uses a Python-based analysis engine and natural language processing (NLP) libraries (e.g., Spacy, BERT). In this step, the input is the legal document transferred to the server, and the output is the identification of the analyzed legal risk items. Data calculations include document syntactic analysis and semantic analysis.

[0111] Step 4:

[0112] The server analyzes legal documents by referencing legal information infrastructure and current legal information databases. Based on the analysis results, it identifies legal risk items and evaluates them. The input is the analyzed document data, and the output is the evaluated risk items. Here, a generative AI model is used to analyze ambiguous clauses.

[0113] Step 5:

[0114] The server converts legal terminology into an intuitively understandable format and generates recommended alternatives. Based on the analyzed risk items, the server automatically generates appropriate alternatives. In this step, the input is the identified legal risk items, and the output is the alternatives written in easily understandable language.

[0115] Step 6:

[0116] The user reviews the presented alternatives on their device. The user considers the content and provides feedback. In this step, the input is the alternatives received from the server, and the output is the feedback information. The user sends the feedback to the server, and final adjustments are made.

[0117] Step 7:

[0118] The server makes final revisions based on user feedback and generates the revised legal document. The input is feedback information, and the output is the final version of the legal document. The final document is then made available for the user to save or download for further use.

[0119] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0120] This invention combines an emotion engine with a system that analyzes legal documents and provides optimal suggestions to the user. This system provides more flexible and appropriate feedback by considering the user's emotional state during the legal document analysis process. First, the user uploads the legal document using a terminal. The terminal converts the document into digital data and sends it to the server.

[0121] Upon receiving data, the server analyzes the document based on legal databases and the latest legal amendments to detect risky clauses. Simultaneously, an emotion engine analyzes user reactions and interactions to recognize the user's emotions. This emotion data is used to tailor the presentation of the analyzed results.

[0122] For example, if the emotion engine determines that the user is confused, the server will translate legal terminology into simpler language and explain alternatives in more detail. Conversely, if the user provides positive feedback, the server will quickly present the same alternative, supporting the user's efficient decision-making.

[0123] Furthermore, users can review proposed revisions and alternatives via their devices and provide emotion-based feedback. This user feedback is collected on a server and used for future improvements. The server then provides an interface tailored to the user's emotions, enhancing the user experience.

[0124] Ultimately, the server generates a legally less risky revised version of the document based on user feedback and sends it to the terminal. The terminal then presents this to the user, who can save or print it. In this way, the system considers user sentiment during the legal document analysis process, resulting in a more effective and user-friendly approach.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] The user operates a terminal to upload legal documents to the system. The terminal uses OCR to convert the uploaded documents into digital text data and sends it to the server.

[0128] Step 2:

[0129] The server receives the digital text data and analyzes the document by referencing legal databases and the latest legal amendment information. This analysis includes detecting potentially risky clauses within the document.

[0130] Step 3:

[0131] In parallel, the server uses an emotion engine to analyze the user's emotional state. This involves detecting the user's input behavior and device usage patterns to determine their emotions.

[0132] Step 4:

[0133] The server processes the analysis results of legal documents based on sentiment evaluations obtained from the sentiment engine. Specifically, it simplifies legal terminology to make it easier for users to understand and adjusts risk assessments.

[0134] Step 5:

[0135] The terminal displays analysis results and alternative solutions from the server to the user. The interface, tailored to the user's emotional state, highlights the risky parts of the document and clearly presents the suggested revisions.

[0136] Step 6:

[0137] The user reviews the proposal via their device and provides feedback on any necessary revisions or alternatives. The device then sends this feedback to the server.

[0138] Step 7:

[0139] The server generates the final revised legal document based on user feedback. It utilizes data from the sentiment engine to create a document that reflects the user's intent.

[0140] Step 8:

[0141] The terminal receives the final revised document and presents it to the user. The user can save or print this document, or request further revisions.

[0142] Through this series of processes, the system analyzes and modifies legal documents while taking user emotions into consideration, providing more personalized support.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] In the analysis of legal documents, conventional technologies fail to consider the user's emotions, resulting in information that is difficult for users to understand. Furthermore, methods for analyzing legal documents in multiple languages ​​and incorporating feedback to improve legal compliance have been limited. To address these challenges, there was a need to develop a system that provides information in an easily understandable format while considering the user's emotions.

[0146] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0147] In this invention, the server includes a device means for inputting legal documents into an information terminal, a device means for converting the input legal documents into information data and transmitting it to a processing device, and a device means for analyzing legal documents by referring to a legal data storage device and recent legal amendment information. This makes it possible to present information while taking into account the user's feelings and to present legally compliant alternatives in an easy-to-understand manner.

[0148] A "legal document" refers to a document that contains provisions and regulations related to the law and has legal effect.

[0149] An "information terminal" is an electronic device used by users to input legal documents and to send, receive, and process data.

[0150] "Information data" refers to data obtained by converting legal documents into a digital format, and is information that is in a format that can be processed by a computer.

[0151] A "processing device" refers to a computer system used to receive and analyze information data.

[0152] A "legal data storage device" refers to a database system that stores legal data and allows it to be accessed as needed.

[0153] "Recent legal amendments" refer to new revisions and updates added to the legal system, and are information intended to ensure the up-to-dateness of legal documents.

[0154] "Analysis" refers to the process of analyzing and evaluating information data from a legal perspective.

[0155] "Emotional analysis" is a method of analyzing a user's psychological state as data and using that information for processing.

[0156] "Presented information" refers to information provided to the user as a result of the analysis, and is presented for the purpose of assisting the user's understanding.

[0157] In this invention, the user first inputs a legal document using a terminal. The terminal converts the uploaded document into digital data using optical character recognition (OCR) technology. This technology can utilize general image processing systems and text conversion software, and is implemented as a dedicated application or module.

[0158] The digital data is then sent to a server. The server analyzes the legal document by referencing legal data storage devices and recent legal amendment information. This process uses natural language processing (NLP) technology and assesses the risks of specific clauses through a generative AI model. At this point, the server utilizes legal databases to perform a more accurate analysis.

[0159] Furthermore, the server uses an emotion engine to analyze the user's emotional state in real time. This emotional state data is used to understand the user's level of comprehension and emotional response. For example, if the emotion engine detects that the user is confused, the server will translate legal jargon into simpler language and generate more detailed alternatives. Conversely, if positive emotions are detected, the server will quickly provide alternatives in their original form.

[0160] Based on the information presented, users review revised versions and alternatives and provide feedback to the server via their device. This feedback helps in making revisions that minimize legal risks. The server then generates the final legal document based on this feedback and sends it to the user's device, allowing them to review, save, or print the final document.

[0161] As a concrete example, the prompt "Analyze the following legal document, identify risky clauses while considering the user's sentiment, and provide appropriate advice" is input into the generating AI model for analysis. Through such prompts, it is possible to provide information tailored to the user.

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] The user selects legal documents using a terminal and uploads them to the system. The input is a physical legal document, which the terminal converts into digital data using optical character recognition (OCR) technology. In this process, the text information within the document is converted from images to text and output as data sent to the server.

[0165] Step 2:

[0166] The server receives digital data from terminals and analyzes it by referencing legal data storage devices and recent legal amendment information. The input is digitized legal documents, and the server interprets the data using natural language processing (NLP) techniques to identify and evaluate risky clauses. The output is the analyzed detailed information and the identification of risk factors.

[0167] Step 3:

[0168] The server activates the emotion engine and analyzes user interaction data to determine the user's emotional state. The input is real-time user response data, which includes facial expressions and tone of voice. Based on this, the server outputs a recognition result of the user's emotional state.

[0169] Step 4:

[0170] The server adjusts the feedback based on the analysis results and the user's emotional state. Specifically, it performs processes such as converting legal terminology into simpler language and refining alternatives. The input is the data obtained in steps 2 and 3, and the output is the adjusted feedback presented to the user.

[0171] Step 5:

[0172] Users review suggested revisions and alternatives provided by the server via their devices and offer feedback based on their own feelings. The input is feedback information received from the server, and users respond with their opinions through a digital interface. This feedback information is sent to the server and output as material for system improvement.

[0173] Step 6:

[0174] The server incorporates user feedback and ultimately generates a legally resistant revised legal document. The input consists of a series of analysis results and user feedback, while the output is the final, revised document sent to the user's terminal. The user can then review, save, or print this document.

[0175] (Application Example 2)

[0176] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0177] Conventional legal information analysis systems have faced challenges in providing feedback that takes into account the user's emotional state when analyzing legal information, making it difficult for users to understand legal terminology and content. Furthermore, there was a need to provide flexible alternative solutions tailored to the user's emotions and to achieve more user-friendly legal information management.

[0178] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0179] This invention includes a server comprising a device for receiving legal information, a device for converting the legal information into an electronic format and transferring it to an information processing device, and a device for analyzing the legal information by referring to a legal data collection and the latest legal amendment information. This makes it possible to adjust the way legal information is presented according to the user's feelings and provide more understandable and user-friendly feedback.

[0180] A "device for receiving legal information" is a device that has the function of acquiring legal documents and data as input.

[0181] A "device that converts legal information into electronic format and transfers it to an information processing device" is a device that has the function of converting acquired legal information into digital data and transmitting it to an information processing device for analysis.

[0182] A "device for analyzing legal information by referring to legal data collections and the latest legal amendment information" is a device that has the function of analyzing legal information using pre-stored legal data and the latest legal amendment information, and extracting specific information.

[0183] A "device that extracts and evaluates risky parts" is a device that identifies parts containing legal issues from analyzed information and has the function of analyzing and evaluating them.

[0184] A "device that simplifies legal terminology and generates appropriate alternatives" is a device that transforms specialized legal terminology into expressions that are generally easy to understand, and further generates alternative solutions as needed.

[0185] A "device that presents generated alternatives to users and receives feedback" is a device that displays proposed alternatives to users and has the function of receiving feedback from users.

[0186] A "device that analyzes the user's emotional state and adjusts the presentation method" is a device that analyzes the user's emotions and optimizes the way information is presented to the user.

[0187] A "device that generates and provides finally corrected legal information" is a device that has the function of generating corrected legal information through analysis and evaluation and providing it to the user.

[0188] In the system implementing this invention, the server is responsible for receiving, analyzing, and presenting legal information. First, the user inputs legal information into the system via a terminal. The input information is converted into digital data by the terminal and sent to the server.

[0189] The server analyzes the input legal information by referencing legal databases and the latest legal amendment information. The software used here includes a "legal document analysis library" for analyzing legal data. During the analysis process, the server extracts and evaluates sections that contain risks. It also uses an emotion engine to analyze the user's emotional state and adjusts the presentation method accordingly. For example, if it is determined that the user is confused, legal terminology will be simplified and explained in an easy-to-understand manner.

[0190] For example, suppose a user submits a mortgage agreement and enters questions about the interest rate into the server. The server analyzes this information, and if it detects the user's anxiety or confusion, it explains the interest rate in simple terms and presents alternative solutions to minimize risk.

[0191] The hardware used consists of a terminal that serves as the interface with the user and a server that processes data. The server uses an "emotion recognition library" and a "legal document analysis library" to analyze the user's emotional state and legal information. By utilizing a generative AI model, continuous improvement can be made based on user feedback.

[0192] An example of a specific prompt message for a generative AI model would be: "If a user expresses anxiety after reviewing a contract, please explain its contents in easy-to-understand language, along with reassuring words."

[0193] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0194] Step 1:

[0195] The user inputs legal information into a terminal. This terminal can handle both paper and electronic information, allowing for scanning or direct digital data input. The input information is converted into digital data within the terminal and transmitted to the server. The input is a legal document, and the output is a legal document in data format.

[0196] Step 2:

[0197] The server prepares the received digital data for analysis. Specifically, it uses a legal document analysis library to analyze the document by querying legal data collections and the latest legal amendment information. As a result of the analysis, it identifies legal risk areas and important clauses. The input is a legal document in data format, and the output is a list of the analyzed clauses.

[0198] Step 3:

[0199] The server uses an emotion recognition library to read the user's emotional state. It collects and analyzes reactions and feedback as the user views documents. The input is user emotion-related data, and the output is an evaluation of the user's emotional state.

[0200] Step 4:

[0201] The server prepares feedback tailored to the user's emotional state. Specifically, it adjusts the wording of legal information presented based on the user's emotions. If the user is confused, it simplifies legal terminology into a more easily understandable form. The input is a list of parsed clauses and an assessment of the user's emotional state, while the output is a feedback statement to be presented to the user.

[0202] Step 5:

[0203] The user views the feedback provided by the server on their terminal. The terminal displays the information from the server and allows the user to provide further opinions and feedback. The input is the information for feedback, and the output is the additional feedback and reactions from the user.

[0204] Step 6:

[0205] Ultimately, the server generates a revised version of the legal document based on the collected user opinions and sentiments. The generated document will have content that minimizes legal risks. The revised document is sent to the user's device, allowing the user to save or print it. The input is user feedback, and the output is the revised legal document.

[0206] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0207] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0208] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0209] [Second Embodiment]

[0210] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0211] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0212] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0213] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0214] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0215] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0216] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0217] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0218] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0219] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0220] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0221] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0222] This invention provides an advanced system for users to analyze legal documents. This system allows for efficient processing of legal documents, from input to final revision. The user first uploads the legal document using a terminal. The terminal converts this document into digital data and sends it to the server.

[0223] The server analyzes documents by cross-referencing them with legal databases and the latest legal amendment information. During this analysis, it detects risky clauses and legal issues within the document. This includes ambiguous wording in contracts and clauses that do not meet international legal standards. The server then simplifies legal terminology and automatically generates user-friendly alternatives. In this way, the server quickly assesses the legal risks of contracts and agreements and presents them to the user.

[0224] Users can review alternative and revised proposals presented via their devices. For example, when a user analyzes an international contract between Japanese and American companies, the server identifies potential legal risks arising from differences between Japanese and American law and presents specific alternatives. In this way, users can revise the contract on the spot based on the presented revisions and send feedback to the server.

[0225] The server then receives feedback from the user, generates a final revised document, and presents it to the user again. The user can save or print this final version. Furthermore, the system supports multilingual legal documents and enables consistent analysis across different language environments. This allows users to ensure international compliance and enhance brand credibility.

[0226] The following describes the processing flow.

[0227] Step 1:

[0228] The user uploads a legal document using their device. The device receives this document and converts it into digital text data using OCR (Optical Character Recognition) technology. The converted data is then sent to the server.

[0229] Step 2:

[0230] The server receives text data and accesses legal databases and the latest legal amendment information. The server analyzes the document's content and detects risks in light of the law. This includes unclear terminology and potentially legally problematic clauses.

[0231] Step 3:

[0232] The server assesses the detected risks and generates alternatives and improvements as needed. The server rephrases legal terminology into a more understandable format and creates a proposal document. This information is provided to the user as a concrete example for accepting legal recommendations.

[0233] Step 4:

[0234] The terminal receives suggestions and alternatives from the server and presents them visually to the user. The user can then review contracts and legal documents based on this information and make necessary revisions. The user then inputs feedback on the revisions into the terminal.

[0235] Step 5:

[0236] The device that receives user feedback sends it to the server. The server generates the final revised legal document based on the feedback.

[0237] Step 6:

[0238] The server sends the final revised document to the terminal. The terminal presents the revised document to the user, who can then save or print it.

[0239] This series of processes allows users to perform legal checks on legal documents efficiently and accurately.

[0240] (Example 1)

[0241] Next, we will describe Example 1. 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."

[0242] Information analysis and evaluation are complex and time-consuming tasks, particularly in legal and technical fields, making it difficult for users to process documents efficiently and accurately. Furthermore, there is a growing need for information processing that supports multiple languages ​​while meeting international standards, but systems to meet these requirements are insufficient.

[0243] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0244] In this invention, the server includes a device for inputting information, a device for converting the input information into data and transmitting it, and a device for analyzing the information by referring to an information database and the latest update information. This enables users to efficiently analyze multilingual information and obtain appropriate alternatives, thereby enabling information processing that meets international standards.

[0245] A "device for inputting information" is a device that has the function of allowing users to provide data to be analyzed to a system using an application or web interface.

[0246] A "device that converts and transmits data" is a device that converts input information into a digital data format and sends it to a server for the necessary analysis process.

[0247] An "information database" is a collection of information used to verify information being analyzed, and is a digital resource that includes legal and technical data.

[0248] "Latest updates" refers to new information that has been changed or added, and in particular includes the latest data on laws and technologies.

[0249] An "analytical device" is a device that uses an information database and the latest updated information to analyze input data and identify risks and other important items.

[0250] "Multilingual information" refers to information expressed in multiple languages ​​and includes data that can be adapted to international contexts.

[0251] An "appropriate alternative" is a proposal that improves upon the original information based on the information obtained through analysis and is presented in a way that is easy for users to understand.

[0252] "International standards" refer to common rules and guidelines across different countries and regions, and are the standards necessary for cross-border business and legal activities.

[0253] This invention provides an advanced system for inputting and analyzing information. The user uploads the information to be analyzed to the system using a terminal. The terminal converts this information into digital data and sends it to a server for analysis. The terminal can accurately extract data from paper and electronic media using text recognition and scanning technologies.

[0254] The server compares this digital data with legal and technical information databases, as well as the latest updates. During the analysis phase, natural language processing (NLP) techniques are used to identify risks and ambiguities within the input data. This allows for the rapid extraction of unclear areas and potential risks based on laws and technical standards.

[0255] Furthermore, the server uses a generative AI model to automatically generate appropriate alternatives for identified risks. This allows for the conversion of technical jargon into simpler language, presenting revised solutions in an easily understandable format for the user. Based on this information, the user can easily review the revised solutions on their device and send feedback back to the server. The server then generates the final information based on the user's feedback, presenting the most suitable content for the user.

[0256] This system supports information in multiple languages ​​and can perform analysis that conforms to international standards. This allows users to process information in a consistent process across different language environments, ensuring international compliance.

[0257] As a concrete example, the prompt text to be input to the generative AI model is as follows:

[0258] "Analyze the risk clauses in the international contract and propose alternatives that comply with the legal standards of the specific country / region."

[0259] This prompt allows the system to efficiently analyze various legal documents and enable necessary legal compliance.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The user uses a terminal to upload information that needs to be analyzed to the system. The input is provided as legal documents, such as PDF or Word files. The terminal utilizes text recognition technology to convert these documents into digital data. This converted digital data is then output and sent to the next process.

[0263] Step 2:

[0264] The server receives the converted digital data. The server then begins analyzing the input data using its information database and the latest updates. This process utilizes natural language processing (NLP) to identify risky elements and ambiguous expressions within the document. The output includes the identified risk elements and analysis results.

[0265] Step 3:

[0266] Based on the analysis results, the server uses a generative AI model to generate alternative solutions that are easy for the user to understand. Identified risk factors and ambiguous expressions are considered as input. The generative AI model then performs data calculations to generate alternative solutions, such as "modified solutions that conform to international standards." The output is a list of easily understandable modified solutions.

[0267] Step 4:

[0268] The user reviews the alternative and corrective suggestions provided by the server through their terminal. From the provided corrective suggestions, the user selects the necessary changes and performs the specific actions to send feedback to the server. The output is feedback data containing the correction instructions given by the user.

[0269] Step 5:

[0270] The server receives feedback from users and generates the final revised information. User feedback data is used as input. Based on this data, the server makes any further necessary adjustments to generate the completed legal document or information. The output is the final version of the document provided to the user.

[0271] Step 6:

[0272] The user uses a terminal to receive the final version of the information provided by the server and to perform operations to save or print it. The input is the completed document provided by the server. The output is the document saved by the user in the desired format (e.g., digital storage or print).

[0273] (Application Example 1)

[0274] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0275] In an international legal environment, analyzing contracts and terms of service is complex, and implementing this analysis, including multilingual support, is difficult. In particular, cross-border electronic payment services require rapid and accurate assessment and response to legal risks. However, traditional methods are insufficient for analyzing such legal information and providing appropriate revisions, potentially leading to legal disputes and damage to brand credibility.

[0276] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0277] In this invention, the server includes means for receiving a collection of legal information, means for analyzing the legal information using a legal information infrastructure and current legal information, and means for identifying legal risk items and evaluating those items. This makes it possible to interpret contract information in international transactions in real time and promote legal compliance.

[0278] A "collection of legal information" refers to a data set that encompasses all legally related information, such as various legal documents, regulations, and contracts.

[0279] "Means of electronic conversion and transfer to remote devices" refers to the process of converting physical or non-electronic legal documents into digital data and transferring them to servers or external devices.

[0280] "Legal information infrastructure and current legal information" refers to a knowledge base that includes databases related to laws and the latest information on legal amendments.

[0281] A "legal risk item" is an element within a legal document that identifies potential legal problems or areas that could lead to future litigation.

[0282] "Intuitively understandable legal terminology" refers to a state where complex legal jargon is replaced with expressions that are easy for the average user to understand.

[0283] Interpretation of "contract information in international transactions" refers to the task of accurately understanding and evaluating information regarding contracts concluded between countries and regions with different legal backgrounds.

[0284] The system of this invention aims to process international contracts safely and efficiently by analyzing legal-related information and evaluating legal risks. This system is realized in a network environment including client devices and servers.

[0285] First, the user inputs an aggregate of legal-related information using a terminal such as a smartphone or a computer. When the user uploads a legal document to the terminal, the terminal uses OCR technology to convert this document into digital data. OCR software such as Tesseract is used for this conversion.

[0286] The converted digital data is sent to the server via the Internet. The server has a Python-based analysis engine and a database for referring to a legal information infrastructure and current regulatory information. Also, legal documents are analyzed using natural language processing (NLP) libraries (e.g., Spacy and BERT) to identify legal risk items.

[0287] For example, when the user uploads a transaction contract between a Japanese company and an overseas company, the server analyzes the differences based on the laws of the corresponding countries. Thereby, risk items are identified, and alternatives are generated and presented to the user in a form that can intuitively understand legal jargon.

[0288] Examples of specific prompt texts include "Please analyze the following legal document, identify legal risks, and generate alternatives." Through this process, the system can perform real-time legal risk assessment and support internationally safe transactions.

[0289] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0290] Step 1:

[0291] The user inputs a collection of legal information using a smartphone or computer. The input information is legal documents in physical or non-electronic form. The device converts these documents into digital data using optical character recognition (OCR) technology. In this step, data processing is performed using OCR software such as Tesseract, and the output is the conversion of image data into text data.

[0292] Step 2:

[0293] The terminal transmits the converted digital data to the server via the internet. The input here is a legal document transcribed into text by OCR, and the output to the server is the data transfer process. This prepares the document for further analysis.

[0294] Step 3:

[0295] The server analyzes the received digital data. The server uses a Python-based analysis engine and natural language processing (NLP) libraries (e.g., Spacy, BERT). In this step, the input is the legal document transferred to the server, and the output is the identification of the analyzed legal risk items. Data calculations include document syntactic analysis and semantic analysis.

[0296] Step 4:

[0297] The server analyzes legal documents by referencing legal information infrastructure and current legal information databases. Based on the analysis results, it identifies legal risk items and evaluates them. The input is the analyzed document data, and the output is the evaluated risk items. Here, a generative AI model is used to analyze ambiguous clauses.

[0298] Step 5:

[0299] The server converts legal terminology into an intuitively understandable format and generates recommended alternatives. Based on the analyzed risk items, the server automatically generates appropriate alternatives. In this step, the input is the identified legal risk items, and the output is the alternatives written in easily understandable language.

[0300] Step 6:

[0301] The user reviews the presented alternatives on their device. The user considers the content and provides feedback. In this step, the input is the alternatives received from the server, and the output is the feedback information. The user sends the feedback to the server, and final adjustments are made.

[0302] Step 7:

[0303] The server makes final revisions based on user feedback and generates the revised legal document. The input is feedback information, and the output is the final version of the legal document. The final document is then made available for the user to save or download for further use.

[0304] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0305] This invention combines an emotion engine with a system that analyzes legal documents and provides optimal suggestions to the user. This system provides more flexible and appropriate feedback by considering the user's emotional state during the legal document analysis process. First, the user uploads the legal document using a terminal. The terminal converts the document into digital data and sends it to the server.

[0306] When the server receives data, it analyzes the document based on the legal database and the latest legal amendment information to detect the clauses at risk. In parallel, the sentiment engine analyzes the user's reactions and interactions to recognize the user's sentiment. This sentiment data is used to adjust the presentation method of the analyzed results.

[0307] For example, if the sentiment engine determines that the user is confused, the server converts legal terms into a more accessible expression and explains the alternatives in more detail. Also, if the user shows positive feedback, the server quickly presents the alternatives as they are to assist the user in making an efficient judgment.

[0308] Furthermore, the user can confirm amendments and alternatives via the terminal and provide sentiment-based feedback. The user's feedback is collected by the server and used for future improvements. The server thereby provides an interface tailored to the user's sentiment and improves the user experience.

[0309] Finally, based on the user's feedback, the server generates a revised document with less legal risk and sends it to the terminal. The terminal presents this to the user, and the user can then save or print it. In this way, the system realizes a more effective and user-friendly response by considering the user's sentiment in the process of analyzing legal documents.

[0310] The following explains the process flow.

[0311] Step 1:

[0312] The user operates the terminal to upload a legal document to the system. The terminal converts the uploaded document into digital text data using OCR and sends it to the server.

[0313] Step 2:

[0314] The server receives the digital text data and analyzes the document by referencing legal databases and the latest legal amendment information. This analysis includes detecting potentially risky clauses within the document.

[0315] Step 3:

[0316] In parallel, the server uses an emotion engine to analyze the user's emotional state. This involves detecting the user's input behavior and device usage patterns to determine their emotions.

[0317] Step 4:

[0318] The server processes the analysis results of legal documents based on sentiment evaluations obtained from the sentiment engine. Specifically, it simplifies legal terminology to make it easier for users to understand and adjusts risk assessments.

[0319] Step 5:

[0320] The terminal displays analysis results and alternative solutions from the server to the user. The interface, tailored to the user's emotional state, highlights the risky aspects of the document and clearly presents the proposed revisions.

[0321] Step 6:

[0322] The user reviews the proposal via their device and provides feedback on any necessary revisions or alternatives. The device then sends this feedback to the server.

[0323] Step 7:

[0324] The server generates the final revised legal document based on user feedback. It utilizes data from the sentiment engine to create a document that reflects the user's intent.

[0325] Step 8:

[0326] The terminal receives the final revised document and presents it to the user. The user can save or print this document, or request further revisions.

[0327] Through this series of processes, the system analyzes and modifies legal documents while taking user emotions into consideration, providing more personalized support.

[0328] (Example 2)

[0329] Next, we will describe Example 2. 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".

[0330] In the analysis of legal documents, conventional technologies fail to consider the user's emotions, resulting in information that is difficult for users to understand. Furthermore, methods for analyzing legal documents in multiple languages ​​and incorporating feedback to improve legal compliance have been limited. To address these challenges, there was a need to develop a system that provides information in an easily understandable format while considering the user's emotions.

[0331] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0332] In this invention, the server includes a device means for inputting legal documents into an information terminal, a device means for converting the input legal documents into information data and transmitting it to a processing device, and a device means for analyzing legal documents by referring to a legal data storage device and recent legal amendment information. This makes it possible to present information while taking into account the user's feelings and to present legally compliant alternatives in an easy-to-understand manner.

[0333] A "legal document" refers to a document that contains provisions and regulations related to the law and has legal effect.

[0334] An "information terminal" is an electronic device used by users to input legal documents and to send, receive, and process data.

[0335] "Information data" refers to data obtained by converting legal documents into a digital format, and is information that is in a format that can be processed by a computer.

[0336] A "processing device" refers to a computer system used to receive and analyze information data.

[0337] A "legal data storage device" refers to a database system that stores legal data and allows it to be accessed as needed.

[0338] "Recent legal amendments" refer to new revisions and updates added to the legal system, and are information intended to ensure the up-to-dateness of legal documents.

[0339] "Analysis" refers to the process of analyzing and evaluating information data from a legal perspective.

[0340] "Emotional analysis" is a method of analyzing a user's psychological state as data and using that information for processing.

[0341] "Presented information" refers to information provided to the user as a result of the analysis, and is presented for the purpose of assisting the user's understanding.

[0342] In this invention, the user first inputs a legal document using a terminal. The terminal converts the uploaded document into digital data using optical character recognition (OCR) technology. This technology can utilize general image processing systems and text conversion software, and is implemented as a dedicated application or module.

[0343] The digital data is then sent to a server. The server analyzes the legal document by referencing legal data storage devices and recent legal amendment information. This process uses natural language processing (NLP) technology and assesses the risks of specific clauses through a generative AI model. At this point, the server utilizes legal databases to perform a more accurate analysis.

[0344] Furthermore, the server uses an emotion engine to analyze the user's emotional state in real time. This emotional state data is used to understand the user's level of comprehension and emotional response. For example, if the emotion engine detects that the user is confused, the server will translate legal jargon into simpler language and generate more detailed alternatives. Conversely, if positive emotions are detected, the server will quickly provide alternatives in their original form.

[0345] Based on the information presented, users review revised versions and alternatives and provide feedback to the server via their device. This feedback helps in making revisions that minimize legal risks. The server then generates the final legal document based on this feedback and sends it to the user's device, allowing them to review, save, or print the final document.

[0346] As a concrete example, the prompt "Analyze the following legal document, identify risky clauses while considering the user's sentiment, and provide appropriate advice" is input into the generating AI model for analysis. Through such prompts, it is possible to provide information tailored to the user.

[0347] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0348] Step 1:

[0349] The user selects legal documents using a terminal and uploads them to the system. The input is a physical legal document, which the terminal converts into digital data using optical character recognition (OCR) technology. In this process, the text information within the document is converted from images to text and output as data sent to the server.

[0350] Step 2:

[0351] The server receives digital data from terminals and analyzes it by referencing legal data storage devices and recent legal amendment information. The input is digitized legal documents, and the server interprets the data using natural language processing (NLP) techniques to identify and evaluate risky clauses. The output is the analyzed detailed information and the identification of risk factors.

[0352] Step 3:

[0353] The server activates the emotion engine and analyzes user interaction data to determine the user's emotional state. The input is real-time user response data, which includes facial expressions and tone of voice. Based on this, the server outputs a recognition result of the user's emotional state.

[0354] Step 4:

[0355] The server adjusts the feedback based on the analysis results and the user's emotional state. Specifically, it performs processes such as converting legal terminology into simpler language and refining alternatives. The input is the data obtained in steps 2 and 3, and the output is the adjusted feedback presented to the user.

[0356] Step 5:

[0357] Users review suggested revisions and alternatives provided by the server via their devices and offer feedback based on their own feelings. The input is feedback information received from the server, and users respond with their opinions through a digital interface. This feedback information is sent to the server and output as material for system improvement.

[0358] Step 6:

[0359] The server incorporates user feedback and ultimately generates a legally resistant revised legal document. The input consists of a series of analysis results and user feedback, while the output is the final, revised document sent to the user's terminal. The user can then review, save, or print this document.

[0360] (Application Example 2)

[0361] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0362] Conventional legal information analysis systems have faced challenges in providing feedback that takes into account the user's emotional state when analyzing legal information, making it difficult for users to understand legal terminology and content. Furthermore, there was a need to provide flexible alternative solutions tailored to the user's emotions and to achieve more user-friendly legal information management.

[0363] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0364] This invention includes a server comprising a device for receiving legal information, a device for converting the legal information into an electronic format and transferring it to an information processing device, and a device for analyzing the legal information by referring to a legal data collection and the latest legal amendment information. This makes it possible to adjust the way legal information is presented according to the user's feelings and provide more understandable and user-friendly feedback.

[0365] A "device for receiving legal information" is a device that has the function of acquiring legal documents and data as input.

[0366] A "device that converts legal information into electronic format and transfers it to an information processing device" is a device that has the function of converting acquired legal information into digital data and transmitting it to an information processing device for analysis.

[0367] A "device for analyzing legal information by referring to legal data collections and the latest legal amendment information" is a device that has the function of analyzing legal information using pre-stored legal data and the latest legal amendment information, and extracting specific information.

[0368] A "device that extracts and evaluates risky parts" is a device that identifies parts containing legal issues from analyzed information and has the function of analyzing and evaluating them.

[0369] A "device that simplifies legal terminology and generates appropriate alternatives" is a device that transforms specialized legal terminology into expressions that are generally easy to understand, and further generates alternative solutions as needed.

[0370] A "device that presents generated alternatives to users and receives feedback" is a device that displays proposed alternatives to users and has the function of receiving feedback from users.

[0371] A "device that analyzes the user's emotional state and adjusts the presentation method" is a device that analyzes the user's emotions and optimizes the way information is presented to the user.

[0372] A "device that generates and provides finally corrected legal information" is a device that has the function of generating corrected legal information through analysis and evaluation and providing it to the user.

[0373] In the system implementing this invention, the server is responsible for receiving, analyzing, and presenting legal information. First, the user inputs legal information into the system via a terminal. The input information is converted into digital data by the terminal and sent to the server.

[0374] The server analyzes the input legal information by referencing legal databases and the latest legal amendment information. The software used here includes a "legal document analysis library" for analyzing legal data. During the analysis process, the server extracts and evaluates sections that contain risks. It also uses an emotion engine to analyze the user's emotional state and adjusts the presentation method accordingly. For example, if it is determined that the user is confused, legal terminology will be simplified and explained in an easy-to-understand manner.

[0375] For example, suppose a user submits a mortgage agreement and enters questions about the interest rate into the server. The server analyzes this information, and if it detects the user's anxiety or confusion, it explains the interest rate in simple terms and presents alternative solutions to minimize risk.

[0376] The hardware used consists of a terminal that serves as the interface with the user and a server that processes data. The server uses an "emotion recognition library" and a "legal document analysis library" to analyze the user's emotional state and legal information. By utilizing a generative AI model, continuous improvement can be made based on user feedback.

[0377] An example of a specific prompt message for a generative AI model would be: "If a user expresses anxiety after reviewing a contract, please explain its contents in easy-to-understand language, along with reassuring words."

[0378] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0379] Step 1:

[0380] The user inputs legal information into a terminal. This terminal can handle both paper and electronic information, allowing for scanning or direct digital data input. The input information is converted into digital data within the terminal and transmitted to the server. The input is a legal document, and the output is a legal document in data format.

[0381] Step 2:

[0382] The server prepares the received digital data for analysis. Specifically, it uses a legal document analysis library to analyze the document by querying legal data collections and the latest legal amendment information. As a result of the analysis, it identifies legal risk areas and important clauses. The input is a legal document in data format, and the output is a list of the analyzed clauses.

[0383] Step 3:

[0384] The server uses an emotion recognition library to read the user's emotional state. It collects and analyzes reactions and feedback as the user views documents. The input is user emotion-related data, and the output is an evaluation of the user's emotional state.

[0385] Step 4:

[0386] The server prepares feedback tailored to the user's emotional state. Specifically, it adjusts the wording of legal information presented based on the user's emotions. If the user is confused, it simplifies legal terminology into a more easily understandable form. The input is a list of parsed clauses and an assessment of the user's emotional state, while the output is a feedback statement to be presented to the user.

[0387] Step 5:

[0388] The user views the feedback provided by the server on their terminal. The terminal displays the information from the server and allows the user to provide further opinions and feedback. The input is the information for feedback, and the output is the additional feedback and reactions from the user.

[0389] Step 6:

[0390] Ultimately, the server generates a revised version of the legal document based on the collected user opinions and sentiments. The generated document will have content that minimizes legal risks. The revised document is sent to the user's device, allowing the user to save or print it. The input is user feedback, and the output is the revised legal document.

[0391] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0392] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0393] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0394] [Third Embodiment]

[0395] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0396] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0397] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0398] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0399] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0400] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0401] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0402] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0403] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0404] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0405] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0406] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0407] This invention provides an advanced system for users to analyze legal documents. This system allows for efficient processing of legal documents, from input to final revision. The user first uploads the legal document using a terminal. The terminal converts this document into digital data and sends it to the server.

[0408] The server analyzes documents by cross-referencing them with legal databases and the latest legal amendment information. During this analysis, it detects risky clauses and legal issues within the document. This includes ambiguous wording in contracts and clauses that do not meet international legal standards. The server then simplifies legal terminology and automatically generates user-friendly alternatives. In this way, the server quickly assesses the legal risks of contracts and agreements and presents them to the user.

[0409] Users can review alternative and revised proposals presented via their devices. For example, when a user analyzes an international contract between Japanese and American companies, the server identifies potential legal risks arising from differences between Japanese and American law and presents specific alternatives. In this way, users can revise the contract on the spot based on the presented revisions and send feedback to the server.

[0410] The server then receives feedback from the user, generates a final revised document, and presents it to the user again. The user can save or print this final version. Furthermore, the system supports multilingual legal documents and enables consistent analysis across different language environments. This allows users to ensure international compliance and enhance brand credibility.

[0411] The following describes the processing flow.

[0412] Step 1:

[0413] The user uploads a legal document using their device. The device receives this document and converts it into digital text data using OCR (Optical Character Recognition) technology. The converted data is then sent to the server.

[0414] Step 2:

[0415] The server receives text data and accesses legal databases and the latest legal amendment information. The server analyzes the document's content and detects risks in light of the law. This includes unclear terminology and potentially legally problematic clauses.

[0416] Step 3:

[0417] The server assesses the detected risks and generates alternatives and improvements as needed. The server rephrases legal terminology into a more understandable format and creates a proposal document. This information is provided to the user as a concrete example for accepting legal recommendations.

[0418] Step 4:

[0419] The terminal receives suggestions and alternatives from the server and presents them visually to the user. The user can then review contracts and legal documents based on this information and make necessary revisions. The user then inputs feedback on the revisions into the terminal.

[0420] Step 5:

[0421] The device that receives user feedback sends it to the server. The server generates the final revised legal document based on the feedback.

[0422] Step 6:

[0423] The server sends the final revised document to the terminal. The terminal presents the revised document to the user, who can then save or print it.

[0424] This series of processes allows users to perform legal checks on legal documents efficiently and accurately.

[0425] (Example 1)

[0426] Next, we will describe Example 1. 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."

[0427] Information analysis and evaluation are complex and time-consuming tasks, particularly in legal and technical fields, making it difficult for users to process documents efficiently and accurately. Furthermore, there is a growing need for information processing that supports multiple languages ​​while meeting international standards, but systems to meet these requirements are insufficient.

[0428] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0429] In this invention, the server includes a device for inputting information, a device for converting the input information into data and transmitting it, and a device for analyzing the information by referring to an information database and the latest update information. This enables users to efficiently analyze multilingual information and obtain appropriate alternatives, thereby enabling information processing that meets international standards.

[0430] A "device for inputting information" is a device that has the function of allowing users to provide data to be analyzed to a system using an application or web interface.

[0431] A "device that converts and transmits data" is a device that converts input information into a digital data format and sends it to a server for the necessary analysis process.

[0432] An "information database" is a collection of information used to verify information being analyzed, and is a digital resource that includes legal and technical data.

[0433] "Latest updates" refers to new information that has been changed or added, and in particular includes the latest data on laws and technologies.

[0434] An "analytical device" is a device that uses an information database and the latest updated information to analyze input data and identify risks and other important items.

[0435] "Multilingual information" refers to information expressed in multiple languages ​​and includes data that can be adapted to international contexts.

[0436] An "appropriate alternative" is a proposal that improves upon the original information based on the information obtained through analysis and is presented in a way that is easy for users to understand.

[0437] "International standards" refer to common rules and guidelines across different countries and regions, and are the standards necessary for cross-border business and legal activities.

[0438] This invention provides an advanced system for inputting and analyzing information. The user uploads the information to be analyzed to the system using a terminal. The terminal converts this information into digital data and sends it to a server for analysis. The terminal can accurately extract data from paper and electronic media using text recognition and scanning technologies.

[0439] The server compares this digital data with legal and technical information databases, as well as the latest updates. During the analysis phase, natural language processing (NLP) techniques are used to identify risks and ambiguities within the input data. This allows for the rapid extraction of unclear areas and potential risks based on laws and technical standards.

[0440] Furthermore, the server uses a generative AI model to automatically generate appropriate alternatives for identified risks. This allows for the conversion of technical jargon into simpler language, presenting revised solutions in an easily understandable format for the user. Based on this information, the user can easily review the revised solutions on their device and send feedback back to the server. The server then generates the final information based on the user's feedback, presenting the most suitable content for the user.

[0441] This system supports information in multiple languages ​​and can perform analysis that conforms to international standards. This allows users to process information in a consistent process across different language environments, ensuring international compliance.

[0442] As a concrete example, the prompt text to be input to the generative AI model is as follows:

[0443] "Analyze the risk clauses in the international contract and propose alternatives that comply with the legal standards of the specific country / region."

[0444] This prompt allows the system to efficiently analyze various legal documents and enable necessary legal compliance.

[0445] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0446] Step 1:

[0447] The user uses a terminal to upload information that needs to be analyzed to the system. The input is provided as legal documents, such as PDF or Word files. The terminal utilizes text recognition technology to convert these documents into digital data. This converted digital data is then output and sent to the next process.

[0448] Step 2:

[0449] The server receives the converted digital data. The server then begins analyzing the input data using its information database and the latest updates. This process utilizes natural language processing (NLP) to identify risky elements and ambiguous expressions within the document. The output includes the identified risk elements and analysis results.

[0450] Step 3:

[0451] Based on the analysis results, the server uses a generative AI model to generate alternative solutions that are easy for the user to understand. Identified risk factors and ambiguous expressions are considered as input. The generative AI model then performs data calculations to generate alternative solutions, such as "modified solutions that conform to international standards." The output is a list of easily understandable modified solutions.

[0452] Step 4:

[0453] The user reviews the alternative and corrective suggestions provided by the server through their terminal. From the provided corrective suggestions, the user selects the necessary changes and performs the specific actions to send feedback to the server. The output is feedback data containing the correction instructions given by the user.

[0454] Step 5:

[0455] The server receives feedback from users and generates the final revised information. User feedback data is used as input. Based on this data, the server makes any further necessary adjustments to generate the completed legal document or information. The output is the final version of the document provided to the user.

[0456] Step 6:

[0457] The user uses a terminal to receive the final version of the information provided by the server and to perform operations to save or print it. The input is the completed document provided by the server. The output is the document saved by the user in the desired format (e.g., digital storage or print).

[0458] (Application Example 1)

[0459] Next, we will explain Application Example 1. In the following explanation, 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."

[0460] In an international legal environment, analyzing contracts and terms of service is complex, and implementing this analysis, including multilingual support, is difficult. In particular, cross-border electronic payment services require rapid and accurate assessment and response to legal risks. However, traditional methods are insufficient for analyzing such legal information and providing appropriate revisions, potentially leading to legal disputes and damage to brand credibility.

[0461] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0462] In this invention, the server includes means for receiving a collection of legal information, means for analyzing the legal information using a legal information infrastructure and current legal information, and means for identifying legal risk items and evaluating those items. This makes it possible to interpret contract information in international transactions in real time and promote legal compliance.

[0463] A "collection of legal information" refers to a data set that encompasses all legally related information, such as various legal documents, regulations, and contracts.

[0464] "Means of electronic conversion and transfer to remote devices" refers to the process of converting physical or non-electronic legal documents into digital data and transferring them to servers or external devices.

[0465] "Legal information infrastructure and current legal information" refers to a knowledge base that includes databases related to laws and the latest information on legal amendments.

[0466] A "legal risk item" is an element within a legal document that identifies potential legal problems or areas that could lead to future litigation.

[0467] "Intuitively understandable legal terminology" refers to a state where complex legal jargon is replaced with expressions that are easy for the average user to understand.

[0468] Interpreting "contractual information in international transactions" refers to the process of accurately understanding and evaluating information regarding contracts concluded between countries and regions with different legal backgrounds.

[0469] The system of this invention aims to process international contracts safely and efficiently by analyzing legal information and assessing legal risks. This system is implemented in a network environment including client devices and servers.

[0470] First, the user inputs a collection of legal information using a device such as a smartphone or computer. Once the user uploads legal documents to the device, the device uses OCR technology to convert these documents into digital data. OCR software such as Tesseract is used for this conversion.

[0471] The converted digital data is transmitted to a server via the internet. The server has a Python-based analysis engine and a database for referencing legal information infrastructure and current legal information. It also uses natural language processing (NLP) libraries (e.g., Spacy and BERT) to analyze legal documents and identify legal risk items.

[0472] For example, if a user uploads a transaction contract between a Japanese company and an overseas company, the server analyzes the differences based on the laws of the relevant countries. This identifies risky clauses and generates and presents alternatives to the user in an intuitively understandable format, avoiding legal jargon.

[0473] Examples of specific prompts include, "Analyze the following legal document, identify legal risks, and generate alternative solutions." Through this process, the system can perform real-time legal risk assessments and support secure international transactions.

[0474] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0475] Step 1:

[0476] The user inputs a collection of legal information using a smartphone or computer. The input information is legal documents in physical or non-electronic form. The device converts these documents into digital data using optical character recognition (OCR) technology. In this step, data processing is performed using OCR software such as Tesseract, and the output is the conversion of image data into text data.

[0477] Step 2:

[0478] The terminal transmits the converted digital data to the server via the internet. The input here is a legal document transcribed into text by OCR, and the output to the server is the data transfer process. This prepares the document for further analysis.

[0479] Step 3:

[0480] The server analyzes the received digital data. The server uses a Python-based analysis engine and natural language processing (NLP) libraries (e.g., Spacy, BERT). In this step, the input is the legal document transferred to the server, and the output is the identification of the analyzed legal risk items. Data calculations include document syntactic analysis and semantic analysis.

[0481] Step 4:

[0482] The server analyzes legal documents by referencing legal information infrastructure and current legal information databases. Based on the analysis results, it identifies legal risk items and evaluates them. The input is the analyzed document data, and the output is the evaluated risk items. Here, a generative AI model is used to analyze ambiguous clauses.

[0483] Step 5:

[0484] The server converts legal terminology into an intuitively understandable format and generates recommended alternatives. Based on the analyzed risk items, the server automatically generates appropriate alternatives. In this step, the input is the identified legal risk items, and the output is the alternatives written in easily understandable language.

[0485] Step 6:

[0486] The user reviews the presented alternatives on their device. The user considers the content and provides feedback. In this step, the input is the alternatives received from the server, and the output is the feedback information. The user sends the feedback to the server, and final adjustments are made.

[0487] Step 7:

[0488] The server makes final revisions based on user feedback and generates the revised legal document. The input is feedback information, and the output is the final version of the legal document. The final document is then made available for the user to save or download for further use.

[0489] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0490] This invention combines an emotion engine with a system that analyzes legal documents and provides optimal suggestions to the user. This system provides more flexible and appropriate feedback by considering the user's emotional state during the legal document analysis process. First, the user uploads the legal document using a terminal. The terminal converts the document into digital data and sends it to the server.

[0491] Upon receiving data, the server analyzes the document based on legal databases and the latest legal amendments to detect risky clauses. Simultaneously, an emotion engine analyzes user reactions and interactions to recognize the user's emotions. This emotion data is used to tailor the presentation of the analyzed results.

[0492] For example, if the emotion engine determines that the user is confused, the server will translate legal terminology into simpler language and explain alternatives in more detail. Conversely, if the user provides positive feedback, the server will quickly present the same alternative, supporting the user's efficient decision-making.

[0493] Furthermore, users can review proposed revisions and alternatives via their devices and provide emotion-based feedback. This user feedback is collected on a server and used for future improvements. The server then provides an interface tailored to the user's emotions, enhancing the user experience.

[0494] Ultimately, the server generates a legally less risky revised version of the document based on user feedback and sends it to the terminal. The terminal then presents this to the user, who can save or print it. In this way, the system considers user sentiment during the legal document analysis process, resulting in a more effective and user-friendly approach.

[0495] The following describes the processing flow.

[0496] Step 1:

[0497] The user operates a terminal to upload legal documents to the system. The terminal uses OCR to convert the uploaded documents into digital text data and sends it to the server.

[0498] Step 2:

[0499] The server receives the digital text data and analyzes the document by referencing legal databases and the latest legal amendment information. This analysis includes detecting potentially risky clauses within the document.

[0500] Step 3:

[0501] In parallel, the server uses an emotion engine to analyze the user's emotional state. This involves detecting the user's input behavior and device usage patterns to determine their emotions.

[0502] Step 4:

[0503] The server processes the analysis results of legal documents based on sentiment evaluations obtained from the sentiment engine. Specifically, it simplifies legal terminology to make it easier for users to understand and adjusts risk assessments.

[0504] Step 5:

[0505] The terminal displays analysis results and alternative solutions from the server to the user. The interface, tailored to the user's emotional state, highlights the risky aspects of the document and clearly presents the proposed revisions.

[0506] Step 6:

[0507] The user reviews the proposal via their device and provides feedback on any necessary revisions or alternatives. The device then sends this feedback to the server.

[0508] Step 7:

[0509] The server generates the final revised legal document based on user feedback. It utilizes data from the sentiment engine to create a document that reflects the user's intent.

[0510] Step 8:

[0511] The terminal receives the final revised document and presents it to the user. The user can save or print this document, or request further revisions.

[0512] Through this series of processes, the system analyzes and modifies legal documents while taking user emotions into consideration, providing more personalized support.

[0513] (Example 2)

[0514] Next, we will describe Example 2. 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."

[0515] In the analysis of legal documents, conventional technologies fail to consider the user's emotions, resulting in information that is difficult for users to understand. Furthermore, methods for analyzing legal documents in multiple languages ​​and incorporating feedback to improve legal compliance have been limited. To address these challenges, there was a need to develop a system that provides information in an easily understandable format while considering the user's emotions.

[0516] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0517] In this invention, the server includes a device means for inputting legal documents into an information terminal, a device means for converting the input legal documents into information data and transmitting it to a processing device, and a device means for analyzing legal documents by referring to a legal data storage device and recent legal amendment information. This makes it possible to present information while taking into account the user's feelings and to present legally compliant alternatives in an easy-to-understand manner.

[0518] A "legal document" refers to a document that contains provisions and regulations related to the law and has legal effect.

[0519] An "information terminal" is an electronic device used by users to input legal documents and to send, receive, and process data.

[0520] "Information data" refers to data obtained by converting legal documents into a digital format, and is information that is in a format that can be processed by a computer.

[0521] A "processing device" refers to a computer system used to receive and analyze information data.

[0522] A "legal data storage device" refers to a database system that stores legal data and allows it to be accessed as needed.

[0523] "Recent legal amendments" refer to new revisions and updates added to the legal system, and are information intended to ensure the up-to-dateness of legal documents.

[0524] "Analysis" refers to the process of analyzing and evaluating information data from a legal perspective.

[0525] "Emotional analysis" is a method of analyzing a user's psychological state as data and using that information for processing.

[0526] "Presented information" refers to information provided to the user as a result of the analysis, and is presented for the purpose of assisting the user's understanding.

[0527] In this invention, the user first inputs a legal document using a terminal. The terminal converts the uploaded document into digital data using optical character recognition (OCR) technology. This technology can utilize general image processing systems and text conversion software, and is implemented as a dedicated application or module.

[0528] The digital data is then sent to a server. The server analyzes the legal document by referencing legal data storage devices and recent legal amendment information. This process uses natural language processing (NLP) technology and assesses the risks of specific clauses through a generative AI model. At this point, the server utilizes legal databases to perform a more accurate analysis.

[0529] Furthermore, the server uses an emotion engine to analyze the user's emotional state in real time. This emotional state data is used to understand the user's level of comprehension and emotional response. For example, if the emotion engine detects that the user is confused, the server will translate legal jargon into simpler language and generate more detailed alternatives. Conversely, if positive emotions are detected, the server will quickly provide alternatives in their original form.

[0530] Based on the information presented, users review revised versions and alternatives and provide feedback to the server via their device. This feedback helps in making revisions that minimize legal risks. The server then generates the final legal document based on this feedback and sends it to the user's device, allowing them to review, save, or print the final document.

[0531] As a concrete example, the prompt "Analyze the following legal document, identify risky clauses while considering the user's sentiment, and provide appropriate advice" is input into the generating AI model for analysis. Through such prompts, it is possible to provide information tailored to the user.

[0532] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0533] Step 1:

[0534] The user selects legal documents using a terminal and uploads them to the system. The input is a physical legal document, which the terminal converts into digital data using optical character recognition (OCR) technology. In this process, the text information within the document is converted from images to text and output as data sent to the server.

[0535] Step 2:

[0536] The server receives digital data from terminals and analyzes it by referencing legal data storage devices and recent legal amendment information. The input is digitized legal documents, and the server interprets the data using natural language processing (NLP) techniques to identify and evaluate risky clauses. The output is the analyzed detailed information and the identification of risk factors.

[0537] Step 3:

[0538] The server activates the emotion engine and analyzes user interaction data to determine the user's emotional state. The input is real-time user response data, which includes facial expressions and tone of voice. Based on this, the server outputs a recognition result of the user's emotional state.

[0539] Step 4:

[0540] The server adjusts the feedback based on the analysis results and the user's emotional state. Specifically, it performs processes such as converting legal terminology into simpler language and refining alternatives. The input is the data obtained in steps 2 and 3, and the output is the adjusted feedback presented to the user.

[0541] Step 5:

[0542] Users review suggested revisions and alternatives provided by the server via their devices and offer feedback based on their own feelings. The input is feedback information received from the server, and users respond with their opinions through a digital interface. This feedback information is sent to the server and output as material for system improvement.

[0543] Step 6:

[0544] The server incorporates user feedback and ultimately generates a legally resistant revised legal document. The input consists of a series of analysis results and user feedback, while the output is the final, revised document sent to the user's terminal. The user can then review, save, or print this document.

[0545] (Application Example 2)

[0546] Next, we will explain application example 2. In the following explanation, 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."

[0547] Conventional legal information analysis systems have faced challenges in providing feedback that takes into account the user's emotional state when analyzing legal information, making it difficult for users to understand legal terminology and content. Furthermore, there was a need to provide flexible alternative solutions tailored to the user's emotions and to achieve more user-friendly legal information management.

[0548] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0549] This invention includes a server comprising a device for receiving legal information, a device for converting the legal information into an electronic format and transferring it to an information processing device, and a device for analyzing the legal information by referring to a legal data collection and the latest legal amendment information. This makes it possible to adjust the way legal information is presented according to the user's feelings and provide more understandable and user-friendly feedback.

[0550] A "device for receiving legal information" is a device that has the function of acquiring legal documents and data as input.

[0551] A "device that converts legal information into electronic format and transfers it to an information processing device" is a device that has the function of converting acquired legal information into digital data and transmitting it to an information processing device for analysis.

[0552] A "device for analyzing legal information by referring to legal data collections and the latest legal amendment information" is a device that has the function of analyzing legal information using pre-stored legal data and the latest legal amendment information, and extracting specific information.

[0553] A "device that extracts and evaluates risky parts" is a device that identifies parts containing legal issues from analyzed information and has the function of analyzing and evaluating them.

[0554] A "device that simplifies legal terminology and generates appropriate alternatives" is a device that transforms specialized legal terminology into expressions that are generally easy to understand, and further generates alternative solutions as needed.

[0555] A "device that presents generated alternatives to users and receives feedback" is a device that displays proposed alternatives to users and has the function of receiving feedback from users.

[0556] A "device that analyzes the user's emotional state and adjusts the presentation method" is a device that analyzes the user's emotions and optimizes the way information is presented to the user.

[0557] A "device that generates and provides finally corrected legal information" is a device that has the function of generating corrected legal information through analysis and evaluation and providing it to the user.

[0558] In the system implementing this invention, the server is responsible for receiving, analyzing, and presenting legal information. First, the user inputs legal information into the system via a terminal. The input information is converted into digital data by the terminal and sent to the server.

[0559] The server analyzes the input legal information by referencing legal databases and the latest legal amendment information. The software used here includes a "legal document analysis library" for analyzing legal data. During the analysis process, the server extracts and evaluates sections that contain risks. It also uses an emotion engine to analyze the user's emotional state and adjusts the presentation method accordingly. For example, if it is determined that the user is confused, legal terminology will be simplified and explained in an easy-to-understand manner.

[0560] For example, suppose a user submits a mortgage agreement and enters questions about the interest rate into the server. The server analyzes this information, and if it detects the user's anxiety or confusion, it explains the interest rate in simple terms and presents alternative solutions to minimize risk.

[0561] The hardware used consists of a terminal that serves as the interface with the user and a server that processes data. The server uses an "emotion recognition library" and a "legal document analysis library" to analyze the user's emotional state and legal information. By utilizing a generative AI model, continuous improvement can be made based on user feedback.

[0562] An example of a specific prompt message for a generative AI model would be: "If a user expresses anxiety after reviewing a contract, please explain its contents in easy-to-understand language, along with reassuring words."

[0563] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0564] Step 1:

[0565] The user inputs legal information into a terminal. This terminal can handle both paper and electronic information, allowing for scanning or direct digital data input. The input information is converted into digital data within the terminal and transmitted to the server. The input is a legal document, and the output is a legal document in data format.

[0566] Step 2:

[0567] The server prepares the received digital data for analysis. Specifically, it uses a legal document analysis library to analyze the document by querying legal data collections and the latest legal amendment information. As a result of the analysis, it identifies legal risk areas and important clauses. The input is a legal document in data format, and the output is a list of the analyzed clauses.

[0568] Step 3:

[0569] The server uses an emotion recognition library to read the user's emotional state. It collects and analyzes reactions and feedback as the user views documents. The input is user emotion-related data, and the output is an evaluation of the user's emotional state.

[0570] Step 4:

[0571] The server prepares feedback tailored to the user's emotional state. Specifically, it adjusts the wording of legal information presented based on the user's emotions. If the user is confused, it simplifies legal terminology into a more easily understandable form. The input is a list of parsed clauses and an assessment of the user's emotional state, while the output is a feedback statement to be presented to the user.

[0572] Step 5:

[0573] The user views the feedback provided by the server on their terminal. The terminal displays the information from the server and allows the user to provide further opinions and feedback. The input is the information for feedback, and the output is the additional feedback and reactions from the user.

[0574] Step 6:

[0575] Ultimately, the server generates a revised version of the legal document based on the collected user opinions and sentiments. The generated document will have content that minimizes legal risks. The revised document is sent to the user's device, allowing the user to save or print it. The input is user feedback, and the output is the revised legal document.

[0576] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0577] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0578] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0579] [Fourth Embodiment]

[0580] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0581] As shown in Figure 7, the 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.

[0582] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0583] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0584] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0585] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0586] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0587] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0588] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0589] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0590] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0591] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0592] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0593] This invention provides an advanced system for users to analyze legal documents. This system allows for efficient processing of legal documents, from input to final revision. The user first uploads the legal document using a terminal. The terminal converts this document into digital data and sends it to the server.

[0594] The server analyzes documents by cross-referencing them with legal databases and the latest legal amendment information. During this analysis, it detects risky clauses and legal issues within the document. This includes ambiguous wording in contracts and clauses that do not meet international legal standards. The server then simplifies legal terminology and automatically generates user-friendly alternatives. In this way, the server quickly assesses the legal risks of contracts and agreements and presents them to the user.

[0595] Users can review alternative and revised proposals presented via their devices. For example, when a user analyzes an international contract between Japanese and American companies, the server identifies potential legal risks arising from differences between Japanese and American law and presents specific alternatives. In this way, users can revise the contract on the spot based on the presented revisions and send feedback to the server.

[0596] The server then receives feedback from the user, generates a final revised document, and presents it to the user again. The user can save or print this final version. Furthermore, the system supports multilingual legal documents and enables consistent analysis across different language environments. This allows users to ensure international compliance and enhance brand credibility.

[0597] The following describes the processing flow.

[0598] Step 1:

[0599] The user uploads a legal document using their device. The device receives this document and converts it into digital text data using OCR (Optical Character Recognition) technology. The converted data is then sent to the server.

[0600] Step 2:

[0601] The server receives text data and accesses legal databases and the latest legal amendment information. The server analyzes the document's content and detects risks in light of the law. This includes unclear terminology and potentially legally problematic clauses.

[0602] Step 3:

[0603] The server assesses the detected risks and generates alternatives and improvements as needed. The server rephrases legal terminology into a more understandable format and creates a proposal document. This information is provided to the user as a concrete example for accepting legal recommendations.

[0604] Step 4:

[0605] The terminal receives suggestions and alternatives from the server and presents them visually to the user. The user can then review contracts and legal documents based on this information and make necessary revisions. The user then inputs feedback on the revisions into the terminal.

[0606] Step 5:

[0607] The device that receives user feedback sends it to the server. The server generates the final revised legal document based on the feedback.

[0608] Step 6:

[0609] The server sends the final revised document to the terminal. The terminal presents the revised document to the user, who can then save or print it.

[0610] This series of processes allows users to perform legal checks on legal documents efficiently and accurately.

[0611] (Example 1)

[0612] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0613] Information analysis and evaluation are complex and time-consuming tasks, particularly in legal and technical fields, making it difficult for users to process documents efficiently and accurately. Furthermore, there is a growing need for information processing that supports multiple languages ​​while meeting international standards, but systems to meet these requirements are insufficient.

[0614] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0615] In this invention, the server includes a device for inputting information, a device for converting the input information into data and transmitting it, and a device for analyzing the information by referring to an information database and the latest update information. This enables users to efficiently analyze multilingual information and obtain appropriate alternatives, thereby enabling information processing that meets international standards.

[0616] A "device for inputting information" is a device that has the function of allowing users to provide data to be analyzed to a system using an application or web interface.

[0617] A "device that converts and transmits data" is a device that converts input information into a digital data format and sends it to a server for the necessary analysis process.

[0618] An "information database" is a collection of information used to verify information being analyzed, and is a digital resource that includes legal and technical data.

[0619] "Latest updates" refers to new information that has been changed or added, and in particular includes the latest data on laws and technologies.

[0620] An "analytical device" is a device that uses an information database and the latest updated information to analyze input data and identify risks and other important items.

[0621] "Multilingual information" refers to information expressed in multiple languages ​​and includes data that can be adapted to international contexts.

[0622] An "appropriate alternative" is a proposal that improves upon the original information based on the information obtained through analysis and is presented in a way that is easy for users to understand.

[0623] "International standards" refer to common rules and guidelines across different countries and regions, and are the standards necessary for cross-border business and legal activities.

[0624] This invention provides an advanced system for inputting and analyzing information. The user uploads the information to be analyzed to the system using a terminal. The terminal converts this information into digital data and sends it to a server for analysis. The terminal can accurately extract data from paper and electronic media using text recognition and scanning technologies.

[0625] The server compares this digital data with legal and technical information databases, as well as the latest updates. During the analysis phase, natural language processing (NLP) techniques are used to identify risks and ambiguities within the input data. This allows for the rapid extraction of unclear areas and potential risks based on laws and technical standards.

[0626] Furthermore, the server uses a generative AI model to automatically generate appropriate alternatives for identified risks. This allows for the conversion of technical jargon into simpler language, presenting revised solutions in an easily understandable format for the user. Based on this information, the user can easily review the revised solutions on their device and send feedback back to the server. The server then generates the final information based on the user's feedback, presenting the most suitable content for the user.

[0627] This system supports information in multiple languages ​​and can perform analysis that conforms to international standards. This allows users to process information in a consistent process across different language environments, ensuring international compliance.

[0628] As a concrete example, the prompt text to be input to the generative AI model is as follows:

[0629] "Analyze the risk clauses in the international contract and propose alternatives that comply with the legal standards of the specific country / region."

[0630] This prompt allows the system to efficiently analyze various legal documents and enable necessary legal compliance.

[0631] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0632] Step 1:

[0633] The user uses a terminal to upload information that needs to be analyzed to the system. The input is provided as legal documents, such as PDF or Word files. The terminal utilizes text recognition technology to convert these documents into digital data. This converted digital data is then output and sent to the next process.

[0634] Step 2:

[0635] The server receives the converted digital data. The server then begins analyzing the input data using its information database and the latest updates. This process utilizes natural language processing (NLP) to identify risky elements and ambiguous expressions within the document. The output includes the identified risk elements and analysis results.

[0636] Step 3:

[0637] Based on the analysis results, the server uses a generative AI model to generate alternative solutions that are easy for the user to understand. Identified risk factors and ambiguous expressions are considered as input. The generative AI model then performs data calculations to generate alternative solutions, such as "modified solutions that conform to international standards." The output is a list of easily understandable modified solutions.

[0638] Step 4:

[0639] The user reviews the alternative and corrective suggestions provided by the server through their terminal. From the provided corrective suggestions, the user selects the necessary changes and performs the specific actions to send feedback to the server. The output is feedback data containing the correction instructions given by the user.

[0640] Step 5:

[0641] The server receives feedback from users and generates the final revised information. User feedback data is used as input. Based on this data, the server makes any further necessary adjustments to generate the completed legal document or information. The output is the final version of the document provided to the user.

[0642] Step 6:

[0643] The user uses a terminal to receive the final version of the information provided by the server and to perform operations to save or print it. The input is the completed document provided by the server. The output is the document saved by the user in the desired format (e.g., digital storage or print).

[0644] (Application Example 1)

[0645] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0646] In an international legal environment, analyzing contracts and terms of service is complex, and implementing this analysis, including multilingual support, is difficult. In particular, cross-border electronic payment services require rapid and accurate assessment and response to legal risks. However, traditional methods are insufficient for analyzing such legal information and providing appropriate revisions, potentially leading to legal disputes and damage to brand credibility.

[0647] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0648] In this invention, the server includes means for receiving a collection of legal information, means for analyzing the legal information using a legal information infrastructure and current legal information, and means for identifying legal risk items and evaluating those items. This makes it possible to interpret contract information in international transactions in real time and promote legal compliance.

[0649] A "collection of legal information" refers to a data set that encompasses all legally related information, such as various legal documents, regulations, and contracts.

[0650] "Means of electronic conversion and transfer to remote devices" refers to the process of converting physical or non-electronic legal documents into digital data and transferring them to servers or external devices.

[0651] "Legal information infrastructure and current legal information" refers to a knowledge base that includes databases related to laws and the latest information on legal amendments.

[0652] A "legal risk item" is an element within a legal document that identifies potential legal problems or areas that could lead to future litigation.

[0653] "Intuitively understandable legal terminology" refers to a state where complex legal jargon is replaced with expressions that are easy for the average user to understand.

[0654] Interpreting "contractual information in international transactions" refers to the process of accurately understanding and evaluating information regarding contracts concluded between countries and regions with different legal backgrounds.

[0655] The system of this invention aims to process international contracts safely and efficiently by analyzing legal information and assessing legal risks. This system is implemented in a network environment including client devices and servers.

[0656] First, the user inputs a collection of legal information using a device such as a smartphone or computer. Once the user uploads legal documents to the device, the device uses OCR technology to convert these documents into digital data. OCR software such as Tesseract is used for this conversion.

[0657] The converted digital data is transmitted to a server via the internet. The server has a Python-based analysis engine and a database for referencing legal information infrastructure and current legal information. It also uses natural language processing (NLP) libraries (e.g., Spacy and BERT) to analyze legal documents and identify legal risk items.

[0658] For example, if a user uploads a transaction contract between a Japanese company and an overseas company, the server analyzes the differences based on the laws of the relevant countries. This identifies risky clauses and generates and presents alternatives to the user in an intuitively understandable format, avoiding legal jargon.

[0659] Examples of specific prompts include, "Analyze the following legal document, identify legal risks, and generate alternative solutions." Through this process, the system can perform real-time legal risk assessments and support secure international transactions.

[0660] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0661] Step 1:

[0662] The user inputs a collection of legal information using a smartphone or computer. The input information is legal documents in physical or non-electronic form. The device converts these documents into digital data using optical character recognition (OCR) technology. In this step, data processing is performed using OCR software such as Tesseract, and the output is the conversion of image data into text data.

[0663] Step 2:

[0664] The terminal transmits the converted digital data to the server via the internet. The input here is a legal document transcribed into text by OCR, and the output to the server is the data transfer process. This prepares the document for further analysis.

[0665] Step 3:

[0666] The server analyzes the received digital data. The server uses a Python-based analysis engine and natural language processing (NLP) libraries (e.g., Spacy, BERT). In this step, the input is the legal document transferred to the server, and the output is the identification of the analyzed legal risk items. Data calculations include document syntactic analysis and semantic analysis.

[0667] Step 4:

[0668] The server analyzes legal documents by referencing legal information infrastructure and current legal information databases. Based on the analysis results, it identifies legal risk items and evaluates them. The input is the analyzed document data, and the output is the evaluated risk items. Here, a generative AI model is used to analyze ambiguous clauses.

[0669] Step 5:

[0670] The server converts legal terminology into an intuitively understandable format and generates recommended alternatives. Based on the analyzed risk items, the server automatically generates appropriate alternatives. In this step, the input is the identified legal risk items, and the output is the alternatives written in easily understandable language.

[0671] Step 6:

[0672] The user reviews the presented alternatives on their device. The user considers the content and provides feedback. In this step, the input is the alternatives received from the server, and the output is the feedback information. The user sends the feedback to the server, and final adjustments are made.

[0673] Step 7:

[0674] The server makes final revisions based on user feedback and generates the revised legal document. The input is feedback information, and the output is the final version of the legal document. The final document is then made available for the user to save or download for further use.

[0675] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0676] This invention combines an emotion engine with a system that analyzes legal documents and provides optimal suggestions to the user. This system provides more flexible and appropriate feedback by considering the user's emotional state during the legal document analysis process. First, the user uploads the legal document using a terminal. The terminal converts the document into digital data and sends it to the server.

[0677] Upon receiving data, the server analyzes the document based on legal databases and the latest legal amendments to detect risky clauses. Simultaneously, an emotion engine analyzes user reactions and interactions to recognize the user's emotions. This emotion data is used to tailor the presentation of the analyzed results.

[0678] For example, if the emotion engine determines that the user is confused, the server will translate legal terminology into simpler language and explain alternatives in more detail. Conversely, if the user provides positive feedback, the server will quickly present the same alternative, supporting the user's efficient decision-making.

[0679] Furthermore, users can review proposed revisions and alternatives via their devices and provide emotion-based feedback. This user feedback is collected on a server and used for future improvements. The server then provides an interface tailored to the user's emotions, enhancing the user experience.

[0680] Ultimately, the server generates a legally less risky revised version of the document based on user feedback and sends it to the terminal. The terminal then presents this to the user, who can save or print it. In this way, the system considers user sentiment during the legal document analysis process, resulting in a more effective and user-friendly approach.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] The user operates a terminal to upload legal documents to the system. The terminal uses OCR to convert the uploaded documents into digital text data and sends it to the server.

[0684] Step 2:

[0685] The server receives the digital text data and analyzes the document by referencing legal databases and the latest legal amendment information. This analysis includes detecting potentially risky clauses within the document.

[0686] Step 3:

[0687] In parallel, the server uses an emotion engine to analyze the user's emotional state. This involves detecting the user's input behavior and device usage patterns to determine their emotions.

[0688] Step 4:

[0689] The server processes the analysis results of legal documents based on sentiment evaluations obtained from the sentiment engine. Specifically, it simplifies legal terminology to make it easier for users to understand and adjusts risk assessments.

[0690] Step 5:

[0691] The terminal displays analysis results and alternative solutions from the server to the user. The interface, tailored to the user's emotional state, highlights the risky aspects of the document and clearly presents the proposed revisions.

[0692] Step 6:

[0693] The user reviews the proposal via their device and provides feedback on any necessary revisions or alternatives. The device then sends this feedback to the server.

[0694] Step 7:

[0695] The server generates the final revised legal document based on user feedback. It utilizes data from the sentiment engine to create a document that reflects the user's intent.

[0696] Step 8:

[0697] The terminal receives the final revised document and presents it to the user. The user can save or print this document, or request further revisions.

[0698] Through this series of processes, the system analyzes and modifies legal documents while taking user emotions into consideration, providing more personalized support.

[0699] (Example 2)

[0700] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0701] In the analysis of legal documents, conventional technologies fail to consider the user's emotions, resulting in information that is difficult for users to understand. Furthermore, methods for analyzing legal documents in multiple languages ​​and incorporating feedback to improve legal compliance have been limited. To address these challenges, there was a need to develop a system that provides information in an easily understandable format while considering the user's emotions.

[0702] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0703] In this invention, the server includes a device means for inputting legal documents into an information terminal, a device means for converting the input legal documents into information data and transmitting it to a processing device, and a device means for analyzing legal documents by referring to a legal data storage device and recent legal amendment information. This makes it possible to present information while taking into account the user's feelings and to present legally compliant alternatives in an easy-to-understand manner.

[0704] A "legal document" refers to a document that contains provisions and regulations related to the law and has legal effect.

[0705] An "information terminal" is an electronic device used by users to input legal documents and to send, receive, and process data.

[0706] "Information data" refers to data obtained by converting legal documents into a digital format, and is information that is in a format that can be processed by a computer.

[0707] A "processing device" refers to a computer system used to receive and analyze information data.

[0708] A "legal data storage device" refers to a database system that stores legal data and allows it to be accessed as needed.

[0709] "Recent legal amendments" refer to new revisions and updates added to the legal system, and are information intended to ensure the up-to-dateness of legal documents.

[0710] "Analysis" refers to the process of analyzing and evaluating information data from a legal perspective.

[0711] "Emotional analysis" is a method of analyzing a user's psychological state as data and using that information for processing.

[0712] "Presented information" refers to information provided to the user as a result of the analysis, and is presented for the purpose of assisting the user's understanding.

[0713] In this invention, the user first inputs a legal document using a terminal. The terminal converts the uploaded document into digital data using optical character recognition (OCR) technology. This technology can utilize general image processing systems and text conversion software, and is implemented as a dedicated application or module.

[0714] The digital data is then sent to a server. The server analyzes the legal document by referencing legal data storage devices and recent legal amendment information. This process uses natural language processing (NLP) technology and assesses the risks of specific clauses through a generative AI model. At this point, the server utilizes legal databases to perform a more accurate analysis.

[0715] Furthermore, the server uses an emotion engine to analyze the user's emotional state in real time. This emotional state data is used to understand the user's level of comprehension and emotional response. For example, if the emotion engine detects that the user is confused, the server will translate legal jargon into simpler language and generate more detailed alternatives. Conversely, if positive emotions are detected, the server will quickly provide alternatives in their original form.

[0716] Based on the information presented, users review revised versions and alternatives and provide feedback to the server via their device. This feedback helps in making revisions that minimize legal risks. The server then generates the final legal document based on this feedback and sends it to the user's device, allowing them to review, save, or print the final document.

[0717] As a concrete example, the prompt "Analyze the following legal document, identify risky clauses while considering the user's sentiment, and provide appropriate advice" is input into the generating AI model for analysis. Through such prompts, it is possible to provide information tailored to the user.

[0718] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0719] Step 1:

[0720] The user selects legal documents using a terminal and uploads them to the system. The input is a physical legal document, which the terminal converts into digital data using optical character recognition (OCR) technology. In this process, the text information within the document is converted from images to text and output as data sent to the server.

[0721] Step 2:

[0722] The server receives digital data from terminals and analyzes it by referencing legal data storage devices and recent legal amendment information. The input is digitized legal documents, and the server interprets the data using natural language processing (NLP) techniques to identify and evaluate risky clauses. The output is the analyzed detailed information and the identification of risk factors.

[0723] Step 3:

[0724] The server activates the emotion engine and analyzes user interaction data to determine the user's emotional state. The input is real-time user response data, which includes facial expressions and tone of voice. Based on this, the server outputs a recognition result of the user's emotional state.

[0725] Step 4:

[0726] The server adjusts the feedback based on the analysis results and the user's emotional state. Specifically, it performs processes such as converting legal terminology into simpler language and refining alternatives. The input is the data obtained in steps 2 and 3, and the output is the adjusted feedback presented to the user.

[0727] Step 5:

[0728] Users review suggested revisions and alternatives provided by the server via their devices and offer feedback based on their own feelings. The input is feedback information received from the server, and users respond with their opinions through a digital interface. This feedback information is sent to the server and output as material for system improvement.

[0729] Step 6:

[0730] The server incorporates user feedback and ultimately generates a legally resistant revised legal document. The input consists of a series of analysis results and user feedback, while the output is the final, revised document sent to the user's terminal. The user can then review, save, or print this document.

[0731] (Application Example 2)

[0732] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0733] Conventional legal information analysis systems have faced challenges in providing feedback that takes into account the user's emotional state when analyzing legal information, making it difficult for users to understand legal terminology and content. Furthermore, there was a need to provide flexible alternative solutions tailored to the user's emotions and to achieve more user-friendly legal information management.

[0734] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0735] This invention includes a server comprising a device for receiving legal information, a device for converting the legal information into an electronic format and transferring it to an information processing device, and a device for analyzing the legal information by referring to a legal data collection and the latest legal amendment information. This makes it possible to adjust the way legal information is presented according to the user's feelings and provide more understandable and user-friendly feedback.

[0736] A "device for receiving legal information" is a device that has the function of acquiring legal documents and data as input.

[0737] A "device that converts legal information into electronic format and transfers it to an information processing device" is a device that has the function of converting acquired legal information into digital data and transmitting it to an information processing device for analysis.

[0738] A "device for analyzing legal information by referring to legal data collections and the latest legal amendment information" is a device that has the function of analyzing legal information using pre-stored legal data and the latest legal amendment information, and extracting specific information.

[0739] A "device that extracts and evaluates risky parts" is a device that identifies parts containing legal issues from analyzed information and has the function of analyzing and evaluating them.

[0740] A "device that simplifies legal terminology and generates appropriate alternatives" is a device that transforms specialized legal terminology into expressions that are generally easy to understand, and further generates alternative solutions as needed.

[0741] A "device that presents generated alternatives to users and receives feedback" is a device that displays proposed alternatives to users and has the function of receiving feedback from users.

[0742] A "device that analyzes the user's emotional state and adjusts the presentation method" is a device that analyzes the user's emotions and optimizes the way information is presented to the user.

[0743] A "device that generates and provides finally corrected legal information" is a device that has the function of generating corrected legal information through analysis and evaluation and providing it to the user.

[0744] In the system implementing this invention, the server is responsible for receiving, analyzing, and presenting legal information. First, the user inputs legal information into the system via a terminal. The input information is converted into digital data by the terminal and sent to the server.

[0745] The server analyzes the input legal information by referencing legal databases and the latest legal amendment information. The software used here includes a "legal document analysis library" for analyzing legal data. During the analysis process, the server extracts and evaluates sections that contain risks. It also uses an emotion engine to analyze the user's emotional state and adjusts the presentation method accordingly. For example, if it is determined that the user is confused, legal terminology will be simplified and explained in an easy-to-understand manner.

[0746] For example, suppose a user submits a mortgage agreement and enters questions about the interest rate into the server. The server analyzes this information, and if it detects the user's anxiety or confusion, it explains the interest rate in simple terms and presents alternative solutions to minimize risk.

[0747] The hardware used consists of a terminal that serves as the interface with the user and a server that processes data. The server uses an "emotion recognition library" and a "legal document analysis library" to analyze the user's emotional state and legal information. By utilizing a generative AI model, continuous improvement can be made based on user feedback.

[0748] An example of a specific prompt message for a generative AI model would be: "If a user expresses anxiety after reviewing a contract, please explain its contents in easy-to-understand language, along with reassuring words."

[0749] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0750] Step 1:

[0751] The user inputs legal information into a terminal. This terminal can handle both paper and electronic information, allowing for scanning or direct digital data input. The input information is converted into digital data within the terminal and transmitted to the server. The input is a legal document, and the output is a legal document in data format.

[0752] Step 2:

[0753] The server prepares the received digital data for analysis. Specifically, it uses a legal document analysis library to analyze the document by querying legal data collections and the latest legal amendment information. As a result of the analysis, it identifies legal risk areas and important clauses. The input is a legal document in data format, and the output is a list of the analyzed clauses.

[0754] Step 3:

[0755] The server uses an emotion recognition library to read the user's emotional state. It collects and analyzes reactions and feedback as the user views documents. The input is user emotion-related data, and the output is an evaluation of the user's emotional state.

[0756] Step 4:

[0757] The server prepares feedback tailored to the user's emotional state. Specifically, it adjusts the wording of legal information presented based on the user's emotions. If the user is confused, it simplifies legal terminology into a more easily understandable form. The input is a list of parsed clauses and an assessment of the user's emotional state, while the output is a feedback statement to be presented to the user.

[0758] Step 5:

[0759] The user views the feedback provided by the server on their terminal. The terminal displays the information from the server and allows the user to provide further opinions and feedback. The input is the information for feedback, and the output is the additional feedback and reactions from the user.

[0760] Step 6:

[0761] Ultimately, the server generates a revised version of the legal document based on the collected user opinions and sentiments. The generated document will have content that minimizes legal risks. The revised document is sent to the user's device, allowing the user to save or print it. The input is user feedback, and the output is the revised legal document.

[0762] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0763] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0764] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0765] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0766] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0767] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0768] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0769] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0770] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0771] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0772] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0773] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0774] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0775] 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.

[0776] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0777] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0778] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0779] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0780] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0781] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0782] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0783] The following is further disclosed regarding the embodiments described above.

[0784] (Claim 1)

[0785] Means of inputting legal documents,

[0786] A means of converting input legal documents into digital data and sending it to a server,

[0787] A means of analyzing legal documents by referring to legal databases and the latest legal amendment information,

[0788] A means of identifying risky clauses and evaluating those clauses,

[0789] A means to simplify legal terminology and generate appropriate alternatives,

[0790] A means of presenting the generated alternatives to the user and receiving feedback,

[0791] The means of generating and providing the final revised legal document,

[0792] A system that includes this.

[0793] (Claim 2)

[0794] A means for handling multilingual legal documents and enabling analysis in different languages, and the system described in claim 1.

[0795] (Claim 3)

[0796] A means for verifying compliance with contracts and regulations and providing indicators for improving brand credibility, and the system according to claim 1.

[0797] "Example 1"

[0798] (Claim 1)

[0799] A device and means for inputting information,

[0800] A device and means for converting input information into data and transmitting it,

[0801] An apparatus and means for analyzing information by referring to an information database and the latest update information,

[0802] A device and means for extracting risk factors and evaluating those factors,

[0803] A device and means for simplifying technical terms and generating appropriate alternatives.

[0804] A device and means for presenting generated alternatives to users and receiving their feedback.

[0805] A device and means for generating and providing the final corrected information,

[0806] A system that includes this.

[0807] (Claim 2)

[0808] A device that supports information in multiple languages ​​and enables analysis in different languages, and the system according to claim 1.

[0809] (Claim 3)

[0810] A device that provides standards for verifying compliance with regulations and standards and for improving reliability, and the system according to claim 1.

[0811] "Application Example 1"

[0812] (Claim 1)

[0813] Means of receiving a collection of legal information,

[0814] A means for electronically converting received information and transferring it to a remote device,

[0815] A means of analyzing legal information using legal information infrastructure and current legal information,

[0816] A means of identifying legal risk items and evaluating those items,

[0817] A means of transforming legal terminology into an intuitively understandable format and constructing the optimal revised plan,

[0818] A means of distributing the generated revision proposals to users and gathering their feedback,

[0819] A means of generating and supplying finally revised legal information,

[0820] A means to interpret contract information in international transactions in real time and promote legal compliance,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] A means for handling legal information consisting of multiple languages ​​and enabling analysis in diverse language environments, and the system according to claim 1.

[0824] (Claim 3)

[0825] A means for evaluating the legal compliance of contract information and provisions and providing criteria for improving the trustworthiness of a company, and the system according to claim 1.

[0826] "Example 2 of combining an emotion engine"

[0827] (Claim 1)

[0828] A device and means for inputting legal documents into an information terminal,

[0829] A device and means for converting input legal documents into information data and transmitting it to a processing device.

[0830] A legal data storage device and a device and means for analyzing legal documents by referring to recent legal amendment information,

[0831] A device and means for analyzing and evaluating the provisions that pose a risk,

[0832] A device and means for making legal terminology easily understandable and for generating appropriate alternatives,

[0833] A device and means for presenting generated alternatives to users and receiving feedback,

[0834] Apparatus and means for generating and providing the final revised legal document,

[0835] A device and means for analyzing user emotions and adjusting the content of presented information based on those emotions.

[0836] A system that includes this.

[0837] (Claim 2)

[0838] A means for handling multilingual legal documents and enabling analysis in different languages, and the system described in claim 1.

[0839] (Claim 3)

[0840] A device for verifying the legal compliance of contract documents and regulations and for providing indicators of creditworthiness, and the system according to claim 1.

[0841] "Application example 2 when combining with an emotional engine"

[0842] (Claim 1)

[0843] Equipped with a device for receiving legal information, and means,

[0844] The system includes a device and means for converting legal information into electronic format and transferring it to an information processing device,

[0845] The device and means are equipped to analyze legal information by referring to legal data collections and the latest legal amendment information.

[0846] The apparatus and means are equipped to extract the parts containing risks and evaluate those parts.

[0847] It is equipped with a device that simplifies legal terminology and generates appropriate alternatives, and means,

[0848] The device includes a mechanism for presenting the generated alternative to the user and receiving a response, and the means are as follows:

[0849] The device includes a mechanism that analyzes the user's emotional state and adjusts the presentation method accordingly.

[0850] The apparatus and means for generating and providing finally revised legal information,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, comprising a device that can handle legal information in multiple languages ​​and enables analysis in different languages.

[0854] (Claim 3)

[0855] The system according to claim 1, comprising a device that verifies compliance with laws and regulations regarding contracts and regulations and provides standards for enhancing the credibility of an organization. [Explanation of symbols]

[0856] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of receiving a collection of legal information, A means for electronically converting received information and transferring it to a remote device, A means of analyzing legal information using legal information infrastructure and current legal information, A means of identifying legal risk items and evaluating those items, A means of transforming legal terminology into an intuitively understandable format and constructing the optimal revised plan, A means of distributing the generated revision proposals to users and gathering their feedback, A means of generating and supplying finally revised legal information, A means to interpret contract information in international transactions in real time and promote legal compliance, A system that includes this.

2. A means for handling legal information consisting of multiple languages ​​and enabling analysis in diverse language environments, and the system according to claim 1.

3. A means for evaluating the legal compliance of contract information and provisions and providing criteria for improving the trustworthiness of a company, and the system according to claim 1.

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