System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a legal consultation input from a user; means for converting the input to text using speech recognition technology; means for analyzing the converted text data and generating legal advice; means for providing the generated legal advice to the user; means for selecting a legal document template in response to the user's document generation request; means for automatically inputting information based on the user's conversation content to the selected template; means for displaying the generated document to the user; and means for storing and outputting the final document.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Creating legal documents requires specialized knowledge, making it difficult for average users to do so, and is time-consuming and costly. Furthermore, hiring a lawyer to help with the process can be slow and inefficient. Therefore, there is a need for an alternative method for businesses, sole proprietors, and nonprofit organizations to quickly and efficiently create accurate legal documents. [Means for solving the problem]

[0005] The present invention is a system that accepts legal consultation input from a user, converts the input into text using speech recognition technology, and analyzes the converted text data to generate legal advice. It provides the generated legal advice to the user, selects a legal document template in response to the user's document generation request, and automatically inputs information based on the user's conversation into the selected template. Furthermore, by including means for displaying the generated document to the user, regenerating it based on correction instructions, and saving and outputting the final document, it is possible to significantly reduce the time and cost required to create legal documents while maintaining professional accuracy.

[0006] "Legal consultation input" means data or information entered by a user into the system when seeking legal advice or counsel.

[0007] "Speech recognition technology" is a technology that converts the voice spoken by a user into text data that a computer can understand.

[0008] "Converting to text" refers to the process of converting voice data into character string data using voice recognition technology.

[0009] "Analyzing text data" refers to the process of analyzing the grammar and meaning of converted text data using natural language processing technology to understand its content.

[0010] "Legal Advice" means advice or recommended actions provided to a User in response to a legal consultation.

[0011] A "document generation request" refers to a user requesting the system to create a specific legal document.

[0012] A "legal document template" refers to a template or format used when creating legal documents.

[0013] "Automatically inputting information" refers to the process in which the system automatically fills in information extracted from the user's conversation into a template.

[0014] "Modification instructions" refer to instructions for corrections or changes made by a user to a generated document.

[0015] "Regeneration" refers to the process of regenerating a document based on correction instructions.

[0016] "Storing and outputting final documents" refers to the process of storing finalized legal documents in digital form and printing or electronically outputting them as needed. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The system of the present invention is an integrated legal support system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system aims to accept legal consultations from users and generate legal documents quickly and accurately based on the consultations.

[0039] Embodiments of the invention

[0040] 1. A user accesses the system

[0041] A user accesses an application in the system using a device (e.g., a smartphone, tablet, or computer). The user enters authentication information (user name and password) on the login screen to log in to the system.

[0042] 2. Legal consultation via voice or text input

[0043] Users can use a microphone to give legal advice by voice, or they can use a keyboard to input their consultation details in text. For example, if a user says, "I want to create an employment contract," this information is entered into the system.

[0044] 3. Speech Recognition and Text Conversion

[0045] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[0046] 4. Text Analysis Using Natural Language Processing

[0047] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[0048] 5. Providing legal advice

[0049] The server searches for appropriate advice from a legal knowledge base and provides it to the user. The generated advice is displayed to the user via the terminal. For example, the advice provided may be, "Employment contracts must include items such as job description, salary, and working hours."

[0050] 6. Document template selection and auto-fill

[0051] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[0052] 7. Viewing and Modifying Documents

[0053] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[0054] 8. Save and print the final document

[0055] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[0056] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (username and password) on the login screen.

[0060] Step 2:

[0061] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[0062] Step 3:

[0063] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[0064] Step 4:

[0065] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[0066] Step 5:

[0067] The server generates legal advice and sends it to the device. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the device. The device displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours."

[0068] Step 6:

[0069] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[0070] Step 7:

[0071] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[0072] Step 8:

[0073] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[0074] Step 9:

[0075] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[0076] Step 10:

[0077] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[0078] Step 11:

[0079] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[0080] Step 12:

[0081] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[0082] Step 13:

[0083] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[0084] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[0085] Example 1

[0086] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0087] Currently, many users face the problem of requiring specialized knowledge when preparing legal documents, which is time-consuming and laborious. Furthermore, there are language barriers when seeking legal advice, and there is a lack of systems that support various input methods, including voice input. Therefore, there is a need for an integrated system that allows users to quickly and accurately prepare legal documents and receive expert support.

[0088] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0089] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for using a natural language processing engine to convert speech data, means for using a legal knowledge base for document generation, and means for adding a digital signature to the document and outputting it. This enables users to easily create legal documents and receive quick and accurate legal advice.

[0090] 1. "Legal Consultation Entry" means an entry made by a User seeking advice on a legal question or issue.

[0091] 2. "Speech recognition technology" refers to technology that analyzes input voice data and converts it into corresponding text data.

[0092] 3. "Text data" means text information converted from audio data.

[0093] 4. A "natural language processing engine" is a software engine that analyzes text data and understands its meaning and structure.

[0094] 5. "Legal Advice" refers to information that provides advice or methods for dealing with a user's legal consultation.

[0095] 6. "Template" means a predefined document model that conforms to a specific format.

[0096] 7. "Legal Document" means a formal document required for legal proceedings or contracts.

[0097] 8. A "legal knowledge base" is a database that compiles legal knowledge such as laws, regulations, and precedents.

[0098] 9. "Voice data" means digital information of voice input using a microphone.

[0099] 10. "Correction Instructions" are requests for changes or corrections made by a User to a Generated Document.

[0100] 11. "Digital Signature" means an electronic signature used to ensure the authenticity and integrity of an electronic document.

[0101] 12. "Preservation" means the act of storing generated documents in digital form.

[0102] 13. "Output" means the act of providing a generated document in the form of printing, digital transmission, or other means.

[0103] The legal support system of this invention is an integrated system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system's purpose is to accept legal consultations from users and generate legal documents quickly and accurately based on those consultations.

[0104] First, a user accesses the system from a device such as a smartphone, tablet, or computer, and authenticates by entering a username and password on the login screen. If authentication is successful, the user can access the system's main screen or dashboard.

[0105] Users can use a microphone to voice their legal consultation or a keyboard to input their consultation details. For example, they can input "I would like to create an employment contract." When this input is transmitted to the system, the device converts the voice data into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text API). The converted text data is then sent directly to the server.

[0106] The server analyzes the received text data using a natural language processing engine (e.g., BERT model) to understand the user's inquiry. This analysis extracts important keywords and phrases and identifies the user's intent. The server then searches for appropriate advice from a legal knowledge base (e.g., a statute database) and provides the generated legal advice to the user. The advice is displayed on the device.

[0107] Next, when a user requests the generation of a document, the server selects an appropriate template from a legal document template database (e.g., the DocuSign template library). This template is automatically filled with information based on the user's consultation. For example, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template.

[0108] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can input correction instructions by text or voice. The server receives these instructions and generates the document again.

[0109] After the user has finalized the document, the server saves it as a PDF as instructed, and optionally digitally signs the document and sends the completed document via email, such as an employment contract being emailed to a new employee.

[0110] For example, consider the following prompt:

[0111] "I want to generate an employment contract for an engineer with a monthly salary of 300,000 yen. The main items are job description, salary, and working hours."

[0112] "I want to generate a one-year rental contract. The monthly rent is 50,000 yen and the security deposit is one month's rent."

[0113] Using such prompts allows the generative AI model to respond more accurately, enabling it to quickly and accurately generate legal documents that meet the user's requirements.

[0114] As such, the system is designed to enable users to easily generate legal documents and receive legal advice quickly and efficiently.

[0115] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0116] Step 1:

[0117] A user accesses the system from a terminal and logs in. Specifically, the user uses a smartphone, tablet, or computer to launch a browser or a dedicated application. They enter their username and password on the system's login screen and click the "Login" button. The server checks the entered authentication information against the database, and if authentication is successful, displays the dashboard screen to the user. The input is the username and password, and the output is a login success message or the dashboard screen.

[0118] Step 2:

[0119] The user inputs their legal consultation by voice or text. Specifically, the user clicks the microphone icon to switch to voice input mode and speaks into the microphone, saying "I would like to create an employment contract," or types "I would like to create an employment contract" into the text box and submits it. The input is voice data or text data, and the output is a screen displaying the content of the legal consultation.

[0120] Step 3:

[0121] The device converts the voice data into text data. The device calls the Google Cloud Speech-to-Text API and sends the voice data acquired from the microphone. The API converts the voice data into text data, and the device receives the converted text. The converted text data is sent to the server. The input is voice data, and the output is text data.

[0122] Step 4:

[0123] The server analyzes the text data. The server passes the received text data to a natural language processing engine (e.g., the BERT model), which analyzes the text and extracts key keywords and phrases. Specifically, it extracts keywords related to "creating an employment contract" and understands the user's intent. The input is text data, and the output is the keywords extracted as a result of the analysis.

[0124] Step 5:

[0125] The server generates legal advice and provides it to the user. The server searches for relevant legal information from a legal database and generates advice appropriate to the user's consultation. The generated advice is sent in text format to the terminal and displayed to the user. Specifically, it displays the message, "Employment contracts must include items such as job description, salary, and working hours." The input is keywords from the analysis results, and the output is the legal advice text.

[0126] Step 6:

[0127] The server selects a document template and automatically fills in the user's information. When the user selects "Generate Document," the server selects an appropriate employment contract template from the DocuSign template library. The server automatically fills in information based on the user's consultation details into the template. Specifically, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template. The input is the text of the legal advice, and the output is the generated document draft.

[0128] Step 7:

[0129] The user checks the generated document and gives instructions for corrections. The generated document is displayed on the user's device, and the user checks the contents. If corrections are necessary, the user clicks on the relevant section and gives instructions for corrections in text or voice. Specifically, the user might instruct, "I want my salary changed to 350,000 yen per month." The server receives the instructions, corrects the document again, and generates it. The input is the user's correction instructions, and the output is the corrected document.

[0130] Step 8:

[0131] The server saves the final document and outputs it as needed. After the user has finalized the document, the server saves it in PDF format as instructed. If necessary, it applies an electronic signature and sends the completed document to the email address specified by the user. Specifically, the completed employment contract is emailed to the new employee. The input is the finalized document, and the output is the saved PDF file and a transmission completion message.

[0132] (Application example 1)

[0133] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0134] Conventional legal document generation systems are often based on simple voice or text input, which can lead to long wait times in physical stores and make it difficult to receive reliable advice online. Furthermore, generating and editing legal documents places a heavy burden on users, making it difficult to provide appropriate legal support, especially in virtual stores.

[0135] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0136] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data to generate legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for providing legal advice within the virtual store, and means for accepting input via smart glasses or a smartphone. This enables users to easily and quickly receive appropriate legal advice even within the virtual store and efficiently generate high-quality legal documents.

[0137] The "means for accepting legal consultation input from the user" is an interface that allows the user to input legal questions or inquiries to the system.

[0138] "Means for converting to text using voice recognition technology" refers to technology for converting voice data entered by a user into text data.

[0139] The "means for analyzing the converted text data and generating legal advice" is a technology that analyzes the text data using natural language processing and generates appropriate legal advice based on the analysis.

[0140] The "means for providing the generated legal advice to the user" is a method for providing the generated legal advice to the user in an easy-to-view format.

[0141] The "means for selecting a legal document template" is a method for automatically selecting an appropriate legal document template based on the content of the user's consultation.

[0142] The "means for automatically inputting information based on the content of a user's conversation into a template" is a technology for automatically inputting information obtained from the content of a user's consultation into a selected template.

[0143] "Means for displaying the generated document to the user and regenerating it based on correction instructions" refers to a technology for displaying the generated document so that the user can check it, and regenerating the document based on the user's correction instructions.

[0144] "Means for saving and outputting the final document" refers to a function for saving the document that has been finally confirmed by the user and outputting it in a format such as printing or generating a PDF as necessary.

[0145] A "means for providing legal advice within a virtual store" is a technology for providing legal advice to a user within a virtual reality environment.

[0146] "Means for accepting input via smart glasses or a smartphone" refers to a method for accepting input from a user using smart glasses or a smartphone.

[0147] This invention is a system for accepting legal consultations from users and generating legal documents quickly and accurately. The system is composed of multiple components, each of which fulfills a specific role.

[0148] First, users access the system using smart glasses or a smartphone and log in by entering their authentication information. Next, users can input legal inquiries by voice or text. For example, they can make specific inquiries such as "I would like to create a rental contract for a store."

[0149] The system converts input voice data into text data using speech recognition technology. This technology is realized, for example, using the speech_recognition module. The converted text data is sent to a server and analyzed using a natural language processing engine (e.g., spaCy). This allows the system to understand the content of the user's legal consultation and generate appropriate legal advice.

[0150] The generated legal advice is then provided to the user via smart glasses or a smartphone, with specific advice such as "The rental agreement must include information such as rent, contract duration, and responsibility for repairs."

[0151] Next, when a user requests the generation of a document, the server automatically selects an appropriate template from a database of legal document templates and automatically populates the template with information based on the user's conversation. This process is performed using, for example, the python-docx module.

[0152] The generated document is displayed to the user, who can check the document contents through smart glasses or a smartphone. If necessary, the user can provide correction instructions, and the server will regenerate the document based on those instructions. After the regenerated document has received final confirmation, it can be digitally signed, saved, printed, or otherwise manipulated. The completed document is saved in PDF format and sent to a designated person.

[0153] For example, if a user asks "I want to create a rental contract for a store," the prompt might look like this:

[0154] Prompt statement:

[0155] "I would like to request a store rental agreement."

[0156] From such prompts, the system can automatically select a rental agreement template and automatically enter the necessary information based on the user's input, generating a high-quality document.

[0157] As described above, the system of the present invention allows users to easily receive legal advice and efficiently generate legal documents within a virtual storefront.

[0158] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0159] Step 1:

[0160] A user accesses the system using smart glasses or a smartphone and enters authentication information to log in. The entered authentication information consists of a username and password, which the system receives and performs an authentication process to establish a logged-in state.

[0161] Input: Username, Password

[0162] Output: Notification of successful or failed login

[0163] Step 2:

[0164] The user inputs legal advice by voice or text. The user can use the microphone on their smart glasses or smartphone to input voice, or use the keyboard to input text. For example, the user can input "I would like to create a rental agreement for a store."

[0165] Input: Audio or text data

[0166] Output: Text data of legal consultation content

[0167] Step 3:

[0168] When the terminal receives voice input, it converts the voice data into text data using voice recognition technology, such as the speech_recognition module, and sends the converted text data to the server.

[0169] Input: Audio data

[0170] Output: Text data

[0171] Step 4:

[0172] The server analyzes the received text data using a natural language processing engine (e.g., spaCy). Specifically, it extracts the legal consultation content from the text data and understands the related information.

[0173] Input: Text data

[0174] Output: Analysis results (legal advice)

[0175] Step 5:

[0176] The server searches for appropriate advice from a legal knowledge base and provides the generated legal advice to the user, such as "The rental agreement must include information such as rent, contract period, and responsibility for repairs."

[0177] Input: Analysis results

[0178] Output: Legal advice

[0179] Step 6:

[0180] When a user requests the generation of a document, the server automatically selects an appropriate template from a legal document template database and automatically inputs information based on the user's conversation into the template. For example, specific information such as "rent: 120,000 yen, contract period: 1 year" can be input.

[0181] Input: User's document generation request, analysis results

[0182] Output: Auto-filled template

[0183] Step 7:

[0184] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can provide instructions for correction, and the server will regenerate the document based on those instructions.

[0185] Input: Auto-filled template, user correction instructions

[0186] Output: The corrected document

[0187] Step 8:

[0188] The finalized document is saved, digitally signed, printed, or output as a PDF, as needed, and the completed document is sent to a designated person.

[0189] Input: Finalized document

[0190] Output: Saved document, PDF file, email

[0191] Through these steps, users can easily and quickly receive legal advice and efficiently generate high-quality legal documents.

[0192] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0193] The system of the present invention is an integrated legal support system that not only receives legal consultations from users, provides legal advice based on the consultations, and generates legal documents, but also recognizes the user's emotions and responds accordingly. This system is realized by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions.

[0194] Embodiments of the invention

[0195] 1. A user accesses the system

[0196] A user accesses the system's application using a device (e.g., smartphone, tablet, computer), enters authentication information (user name and password) on the login screen, and logs in to the system.

[0197] 2. Legal consultation via voice or text input

[0198] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their legal advice by text. For example, if a user says, "I would like to create an employment contract," this information is entered into the system.

[0199] 3. Speech Recognition and Text Conversion

[0200] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[0201] 4. Text Analysis Using Natural Language Processing

[0202] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[0203] 5. Analysis of user emotions using an emotion recognition engine

[0204] The server uses an emotion engine to analyze the user's emotions based on the user's voice data and text data. For example, if the user is feeling nervous or anxious, the emotion engine will recognize this.

[0205] 6. Providing legal advice

[0206] The server generates appropriate legal advice based on the user's legal consultation content and emotional state and sends it to the terminal. The terminal then displays the generated advice to the user. For example, the advice provided may include "job description, salary, and working hours in the employment contract."

[0207] 7. Document template selection and auto-fill

[0208] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[0209] 8. Viewing and Modifying Documents

[0210] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[0211] 9. Save and print the final document

[0212] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[0213] In this way, by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions, the system can quickly and efficiently assist users in creating legal documents and generate high-quality legal documents that take the user's emotions into consideration.

[0214] The processing flow will be explained below.

[0215] Step 1:

[0216] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (user name and password) on the login screen.

[0217] Step 2:

[0218] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[0219] Step 3:

[0220] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[0221] Step 4:

[0222] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[0223] Step 5:

[0224] The server uses an emotion recognition engine to analyze the user's emotions. The server analyzes the user's emotions based on voice and text data. For example, it recognizes emotions such as "I'm in a hurry" or "I'm anxious."

[0225] Step 6:

[0226] The server generates legal advice and sends it to the terminal. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the terminal. The terminal displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours." It takes the user's feelings into consideration and uses gentle language or provides brief explanations if the user is in a hurry.

[0227] Step 7:

[0228] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[0229] Step 8:

[0230] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[0231] Step 9:

[0232] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[0233] Step 10:

[0234] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[0235] Step 11:

[0236] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[0237] Step 12:

[0238] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[0239] Step 13:

[0240] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[0241] Step 14:

[0242] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[0243] In this way, the system supports users in creating legal documents quickly and efficiently, and enables the generation of high-quality legal documents that also take the user's feelings into consideration.

[0244] Example 2

[0245] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0246] Conventional legal support systems have difficulty not only accurately analyzing the consultation content provided by users and generating appropriate legal advice, but also responding while taking the user's emotions into consideration. Furthermore, the accuracy and efficiency of the generated legal documents are insufficient, and users have to spend a lot of time reviewing and revising the documents. Furthermore, few systems support both voice input and keyboard input, which reduces user convenience. There is a need to provide an integrated system that can solve these issues and provide users with high-quality, prompt legal support.

[0247] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for accepting legal consultation input from a user; means for converting the input into text using speech recognition technology; means for analyzing the converted text data using a natural language processing engine to generate legal advice; means for determining the user's emotional state based on the analyzed text data and an emotion recognition engine; means for providing the generated legal advice to the user; means for selecting a legal document template in response to the user's document generation request; means for automatically inputting information based on the user's conversation content into the selected template; means for displaying the generated document to the user and regenerating it based on correction instructions; and means for saving and outputting the final document. This makes it possible to respond to various input methods from users and quickly provide high-quality legal support that takes their emotional state into consideration.

[0248] The "means for accepting input of legal consultation from the user" is a means for receiving the content of the consultation when the user makes a legal consultation to the system.

[0249] "Means for converting to text using speech recognition technology" refers to means that use technology to convert voice data uttered by a user into text data.

[0250] The "means for generating legal advice by analyzing using a natural language processing engine" is a means for generating legal advice based on the content of the user's consultation using a natural language processing engine that analyzes text data.

[0251] "Means for determining the emotional state of a user based on an emotion recognition engine" refers to means for determining the emotional state of a user (e.g., tension, anxiety, relief) using an emotion recognition engine based on the user's voice or text data.

[0252] The "means for providing generated legal advice to a user" refers to a means for conveying generated legal advice to a user.

[0253] The "means for selecting a legal document template" is a means for selecting, from a database, a legal document template that is suitable for a user's document generation request.

[0254] The "means for automatically inputting information based on the content of the user's conversation" is a means for automatically inputting information based on the content of the user's consultation or request into a selected template.

[0255] The "means for displaying the generated document to the user and regenerating it based on a correction instruction" refers to a means for displaying the generated document to the user and regenerating the document based on a correction instruction from the user.

[0256] The "means for saving and outputting the final document" refers to the means for digitally signing, saving, printing, emailing, etc. the final document.

[0257] This invention relates to an integrated legal support system that not only receives legal consultation input from users, provides legal advice based on that input, and generates legal documents, but also recognizes the user's emotions and responds appropriately. Specifically, this system is realized by combining voice recognition technology, a natural language processing engine, an emotion recognition engine, and an automatic document generation function.

[0258] The hardware required to implement this system includes the user's device (e.g., smartphone, tablet, computer) and server. The software uses speech recognition technology (e.g., Google Cloud Speech-to-Text), natural language processing engines (e.g., spaCy, BERT), emotion recognition engines (e.g., IBM Watson Tone Analyzer), and automatic document generation functions.

[0259] System Operation Overview

[0260] 1. A user accesses the system

[0261] A user accesses the system's application using a smartphone, tablet, or computer and enters their credentials on the login screen. The server validates the information and redirects the user to the main menu screen.

[0262] 2. Legal consultation via voice or text input

[0263] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their consultation details in text. For example, if a user says, "I would like to create an employment contract," that information is entered into the system.

[0264] 3. Speech Recognition and Text Conversion

[0265] The device captures the user's voice and converts it to text using Google Cloud Speech-to-Text, which is then sent to a server.

[0266] 4. Text Analysis Using Natural Language Processing

[0267] The server analyzes the received text data using a natural language processing engine (e.g., spaCy, BERT) and generates legal advice by extracting relevant information based on the user's input (e.g., "Create an employment contract").

[0268] 5. Analysis of user emotions using an emotion recognition engine

[0269] The server inputs voice and text data into IBM Watson Tone Analyzer, which analyzes the user's emotional state (e.g., "tension" or "anxiety").

[0270] 6. Providing legal advice

[0271] The server generates legal advice based on the analysis results and sends it to the device, which then displays it to the user. For example, the advice might be, "Employment contracts must include job descriptions, salary, and working hours."

[0272] 7. Document template selection and auto-fill

[0273] When a user requests the generation of a legal document, the server selects an appropriate template and automatically inputs the user's conversation content (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") into that template.

[0274] 8. Viewing and Modifying Documents

[0275] The generated document is displayed on the terminal, and the user can check the contents. If necessary, they can provide instructions for correction, and the server will regenerate the document based on those instructions.

[0276] 9. Save and print the final document

[0277] The user performs a final check and then saves the completed document, digitally signs it, prints it, sends it by email, etc. The server executes these operations and saves the final version of the document.

[0278] Specific examples

[0279] For example, by entering the following prompt, the system can efficiently generate legal documents based on the user's needs:

[0280] "I would like to create an employment contract. I would like to be employed as an engineer with a monthly salary of 300,000 yen."

[0281] This prompt allows users to easily create the necessary legal documents and receive appropriate legal advice.

[0282] As described above, this system integrates voice recognition technology, a natural language processing engine, an emotion recognition engine, and automatic document generation functions, enabling it to provide users with high-quality, efficient legal support.

[0283] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0284] Step 1: User accesses the system

[0285] Input: A user accesses the system's application using a smartphone, tablet, or computer and enters their username and password on the login screen.

[0286] Specific operation: The authentication information entered by the user is sent to the server via the terminal.

[0287] Data processing: The server checks the authentication information against a database to verify whether the user has a valid account.

[0288] Output: If the validation is successful, the server redirects the user to the main menu screen.

[0289] Step 2: Legal consultation via voice or text

[0290] Input: The user selects the "Legal Consultation" option on the main menu screen and then either uses the microphone to speak or uses the keyboard to enter text.

[0291] Specific behavior: The user speaks "I would like to create an employment contract" or types "I would like to create an employment contract" in text.

[0292] Output: The audio or text data is saved to the device.

[0293] Step 3: Speech recognition and text conversion

[0294] Input: Audio data stored on the device.

[0295] Specific operation: The device uses voice recognition technology (e.g., Google Cloud Speech-to-Text) to convert voice data into text data.

[0296] Data Processing: The process of analyzing the audio data and converting it into corresponding text takes place.

[0297] Output: The converted text data (e.g., "I would like to create an employment contract") is sent to the server.

[0298] Step 4: Text analysis using natural language processing

[0299] Input: The text data sent to the server.

[0300] Specific operation: The server analyzes the received text data using a natural language processing (NLP) engine (e.g., spaCy, BERT).

[0301] Data processing: Extract the user's inquiry content (e.g., "drafting an employment contract") from the text data and search for related legal information.

[0302] Output: Legal advice data based on the analysis results.

[0303] Step 5: Analyze user emotions using an emotion recognition engine

[0304] Input: Audio and text data.

[0305] Specific operation: The server inputs the voice data and text data into an emotion recognition engine (e.g., IBM Watson Tone Analyzer).

[0306] Data processing: Analyze the user's emotional state (e.g., "tension" or "anxiety") from the input data and assign an emotional tag.

[0307] Output: User's emotional state data.

[0308] Step 6: Providing legal advice

[0309] Input: Analysis results of the natural language processing engine and the emotion recognition engine.

[0310] Specific behavior: The server generates appropriate legal advice based on these results.

[0311] Data processing: The generated legal advice is customized to take into account the user's emotional state.

[0312] Output: Customized legal advice is sent to the terminal, which displays it to the user, for example, "Employment contracts must include job descriptions, salary, and working hours."

[0313] Step 7: Select a document template and auto-fill

[0314] Input: The user's document generation request.

[0315] Specific operation: The server selects a template suitable for the user's request from a database of legal document templates.

[0316] Data processing: The content of the user's conversation (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") is automatically entered into the selected template.

[0317] Output: Completed auto-filled legal document template data.

[0318] Step 8: View and modify the document

[0319] Input: Auto-filled legal document template data.

[0320] Specific operation: The generated document is displayed on the terminal and the user checks the contents.

[0321] Data processing: The user inputs correction instructions as needed, which are then sent to the server.

[0322] Output: Document data that reflects the user's correction instructions.

[0323] Step 9: Save and print the final document

[0324] Input: The corrected document data.

[0325] Specific actions: The user performs a final review and specifies actions such as saving the completed document, digitally signing it, printing it, or sending it by email.

[0326] Data processing: The server generates a document in the specified format (e.g., PDF) and sends the data to the specified storage or destination.

[0327] Output: The final legal document data is saved and sent as needed.

[0328] (Application example 2)

[0329] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] Conventional legal consultation systems can accept legal consultations from users, perform speech recognition and text analysis, and provide legal advice, but they have the problem of being unable to respond to the user's emotions. Even when a user is feeling anxious or nervous, conventional systems are unable to recognize and respond to those emotions, creating a need for improved user experience. Furthermore, when it comes to generating legal documents, simply selecting a template and automatically entering information is not enough; a more user-friendly system that adapts to the user's emotional state is also needed.

[0331] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0332] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for analyzing the user's emotions, means for adjusting a response based on the analyzed emotions, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, and means for saving and outputting the final document, thereby enabling optimal legal advice and document generation according to the user's emotional state.

[0333] "Legal consultation input" refers to the act of a user speaking to or inputting information about a legal problem or question into the system, and the content of that information.

[0334] "Speech recognition technology" is a technology that converts voice data into text data.

[0335] "Text data" refers to text information converted using voice recognition technology.

[0336] "Legal Advice" means professional opinions and suggestions provided based on a User's legal consultation input.

[0337] "Emotion analysis" is a technology that reads emotions from a user's voice data or text data and classifies those emotions.

[0338] "Adjusting response" refers to changing the legal advice provided or the way in which a conversation is conducted based on the analyzed user's emotions.

[0339] A "document generation request" refers to a user requesting the system to generate a specific legal document.

[0340] "Legal Document Template" refers to a template for creating a specific legal document.

[0341] "Auto-filling information" refers to automatically filling in required information into a selected template based on the user's input.

[0342] "Modification instructions" refer to instructions that a user requests to change a generated document.

[0343] "Final Document" refers to the completed legal document after user review and correction.

[0344] "Storing and outputting" refers to storing the final document in digital form and providing it to the user, such as by physically printing it, if necessary.

[0345] System configuration

[0346] The system according to the present invention comprises the following hardware and software. The hardware includes a device (such as a smartphone or a head-mounted display (HMD)) and a microphone for the user to receive legal consultation. The software includes speech recognition technology, an emotion analysis engine, a natural language processing engine, and an automatic document generation function.

[0347] Program Overview

[0348] 1. Speech Recognition Technology

[0349] The device receives voice input from the user and converts the voice data into text data using voice recognition technology (e.g., Python's speech_recognition library).

[0350] 2. Natural Language Processing

[0351] The server analyzes the converted text data using a natural language processing engine (e.g., NLPProcessor) and generates legal advice based on the legal consultation content.

[0352] 3. Emotion analysis

[0353] The server analyzes the user's emotions from the voice and text data using an emotion analysis engine (e.g., EmotionRecognizer). Based on the analyzed emotion data, the system adjusts the content of the legal advice and documents it generates.

[0354] 4. Generating Legal Documents

[0355] In response to a user's document generation request, the server selects a legal document template (e.g., LegalDocumentGenerator) and automatically fills in information based on the user's conversation.

[0356] 5. Viewing and Modifying Documents

[0357] The generated document is displayed to the user, and if the user requests corrections, it is regenerated. By repeating this process, the final document is completed.

[0358] 6. Saving and printing the final document

[0359] After the final confirmation, the document is digitally signed, saved, printed, etc. based on the user's instructions. The completed document is saved in PDF format and provided to the user.

[0360] Specific examples

[0361] When a user uses their smartphone to voice-input "I want to create a divorce agreement," the system converts the speech into text. The natural language processing engine then analyzes the text and generates the legal advice the user is seeking. At the same time, the sentiment analysis engine analyzes the user's emotions and, if it determines that the user is feeling anxious, makes suggestions to alleviate the user's anxiety.

[0362] An example of a prompt for a generative AI model is:

[0363] User Input:

[0364] I want to create a divorce agreement

[0365] Please tell me the details of the division of assets

[0366] Generated AI prompt:

[0367] "User wants to create divorce agreement. Feeling uneasy. Please provide appropriate legal advice and how to generate the document. Please include example sentences."

[0368] As in this example, the system can accept legal consultations from users, provide appropriate legal advice in real time, respond to their emotions, and generate, save, and output the final legal documents.

[0369] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0370] Step 1:

[0371] The user inputs the consultation details into the terminal by voice or text.

[0372] Input: The user speaks using a microphone or enters text using a keyboard.

[0373] Processing: The device uses voice recognition technology to convert the voice data into text data. If the input is text, it is treated as text data.

[0374] Output: Sent to the server as text data.

[0375] Step 2:

[0376] The server receives the text data and analyzes it using a natural language processing engine.

[0377] Input: Text data sent from the terminal.

[0378] Processing: The server's natural language processing engine analyzes the text data and extracts the user's legal consultation details.

[0379] Output: Extracted legal consultation content.

[0380] Step 3:

[0381] The server analyzes the user's emotions and obtains the results.

[0382] Input: User voice and text data.

[0383] Processing: The server's emotion analysis engine analyzes the audio and text data to recognize emotional states (e.g., anxiety, tension).

[0384] Output: Emotion analysis results.

[0385] Step 4:

[0386] The server generates appropriate legal advice based on the content of the legal consultation and the results of sentiment analysis.

[0387] Input: Legal consultation content and sentiment analysis results.

[0388] Processing: A natural language processing engine integrates legal consultation content with sentiment analysis results to generate tailored legal advice for the user.

[0389] Output: The generated legal advice.

[0390] Step 5:

[0391] The server transmits legal advice to the terminal and provides it to the user.

[0392] Input: The generated legal advice.

[0393] Processing: The server sends the legal advice to the device, which displays it to the user.

[0394] Output: The legal advice that is displayed to the user.

[0395] Step 6:

[0396] The user makes a document generation request.

[0397] Input: The user's document generation request.

[0398] Process: The user sends a document generation request to the server through the terminal.

[0399] Output: A request to the server to generate the document.

[0400] Step 7:

[0401] The server selects the appropriate legal document template and auto-fills the information.

[0402] Input: Document generation request and user consultation.

[0403] Processing: The server selects an appropriate template from a legal document template database and automatically fills in information based on the user's conversation.

[0404] Output: The generated legal document.

[0405] Step 8:

[0406] The server sends the generated document to the terminal and displays it to the user.

[0407] Input: The generated legal document.

[0408] Process: The server sends the document to the terminal, which displays it to the user.

[0409] Output: The document that is displayed to the user.

[0410] Step 9:

[0411] The user checks the document and gives instructions for corrections as necessary.

[0412] Input: The user checks the displayed document and gives instructions for correction if necessary.

[0413] Processing: The server regenerates the document based on the user's correction instructions.

[0414] Output: The corrected document.

[0415] Step 10:

[0416] The server stores and outputs the final document.

[0417] Input: Final revised document.

[0418] Processing: The server stores the final document digitally and prints or emails it as needed.

[0419] Output: storing in digital form or providing to users.

[0420] The above steps enable optimal legal advice and document generation according to the user's emotional state.

[0421] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0422] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0423] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0424] [Second embodiment]

[0425] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0426] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0427] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0428] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0429] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0430] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0431] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0432] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0433] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0434] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0435] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0436] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0437] The system of the present invention is an integrated legal support system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system aims to accept legal consultations from users and generate legal documents quickly and accurately based on the consultations.

[0438] Embodiments of the invention

[0439] 1. A user accesses the system

[0440] A user accesses an application in the system using a device (e.g., a smartphone, tablet, or computer). The user enters authentication information (user name and password) on the login screen to log in to the system.

[0441] 2. Legal consultation via voice or text input

[0442] Users can use a microphone to give legal advice by voice, or they can use a keyboard to input their consultation details in text. For example, if a user says, "I want to create an employment contract," this information is entered into the system.

[0443] 3. Speech Recognition and Text Conversion

[0444] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[0445] 4. Text Analysis Using Natural Language Processing

[0446] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[0447] 5. Providing legal advice

[0448] The server searches for appropriate advice from a legal knowledge base and provides it to the user. The generated advice is displayed to the user via the terminal. For example, the advice provided may be, "Employment contracts must include items such as job description, salary, and working hours."

[0449] 6. Document template selection and auto-fill

[0450] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[0451] 7. Viewing and Modifying Documents

[0452] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[0453] 8. Save and print the final document

[0454] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[0455] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[0456] The processing flow will be explained below.

[0457] Step 1:

[0458] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (username and password) on the login screen.

[0459] Step 2:

[0460] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[0461] Step 3:

[0462] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[0463] Step 4:

[0464] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[0465] Step 5:

[0466] The server generates legal advice and sends it to the device. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the device. The device displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours."

[0467] Step 6:

[0468] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[0469] Step 7:

[0470] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[0471] Step 8:

[0472] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[0473] Step 9:

[0474] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[0475] Step 10:

[0476] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[0477] Step 11:

[0478] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[0479] Step 12:

[0480] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[0481] Step 13:

[0482] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[0483] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[0484] Example 1

[0485] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0486] Currently, many users face the problem of requiring specialized knowledge when preparing legal documents, which is time-consuming and laborious. Furthermore, there are language barriers when seeking legal advice, and there is a lack of systems that support various input methods, including voice input. Therefore, there is a need for an integrated system that allows users to quickly and accurately prepare legal documents and receive expert support.

[0487] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0488] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for using a natural language processing engine to convert speech data, means for using a legal knowledge base for document generation, and means for adding a digital signature to the document and outputting it. This enables users to easily create legal documents and receive quick and accurate legal advice.

[0489] 1. "Legal Consultation Entry" means an entry made by a User seeking advice on a legal question or issue.

[0490] 2. "Speech recognition technology" refers to technology that analyzes input voice data and converts it into corresponding text data.

[0491] 3. "Text data" means text information converted from audio data.

[0492] 4. A "natural language processing engine" is a software engine that analyzes text data and understands its meaning and structure.

[0493] 5. "Legal Advice" refers to information that provides advice or methods for dealing with a user's legal consultation.

[0494] 6. "Template" means a predefined document model that conforms to a specific format.

[0495] 7. "Legal Document" means a formal document required for legal proceedings or contracts.

[0496] 8. A "legal knowledge base" is a database that compiles legal knowledge such as laws, regulations, and precedents.

[0497] 9. "Voice data" means digital information of voice input using a microphone.

[0498] 10. "Correction Instructions" are requests for changes or corrections made by a User to a Generated Document.

[0499] 11. "Digital Signature" means an electronic signature used to ensure the authenticity and integrity of an electronic document.

[0500] 12. "Preservation" means the act of storing generated documents in digital form.

[0501] 13. "Output" means the act of providing a generated document in the form of printing, digital transmission, or other means.

[0502] The legal support system of this invention is an integrated system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system's purpose is to accept legal consultations from users and generate legal documents quickly and accurately based on those consultations.

[0503] First, a user accesses the system from a device such as a smartphone, tablet, or computer, and authenticates by entering a username and password on the login screen. If authentication is successful, the user can access the system's main screen or dashboard.

[0504] Users can use a microphone to voice their legal consultation or a keyboard to input their consultation details. For example, they can input "I would like to create an employment contract." When this input is transmitted to the system, the device converts the voice data into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text API). The converted text data is then sent directly to the server.

[0505] The server analyzes the received text data using a natural language processing engine (e.g., BERT model) to understand the user's inquiry. This analysis extracts important keywords and phrases and identifies the user's intent. The server then searches for appropriate advice from a legal knowledge base (e.g., a statute database) and provides the generated legal advice to the user. The advice is displayed on the device.

[0506] Next, when a user requests the generation of a document, the server selects an appropriate template from a legal document template database (e.g., the DocuSign template library). This template is automatically filled with information based on the user's consultation. For example, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template.

[0507] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can input correction instructions by text or voice. The server receives these instructions and generates the document again.

[0508] After the user has finalized the document, the server saves it as a PDF as instructed, and optionally digitally signs the document and sends the completed document via email, such as an employment contract being emailed to a new employee.

[0509] For example, consider the following prompt:

[0510] "I want to generate an employment contract for an engineer with a monthly salary of 300,000 yen. The main items are job description, salary, and working hours."

[0511] "I want to generate a one-year rental contract. The monthly rent is 50,000 yen and the security deposit is one month's rent."

[0512] Using such prompts allows the generative AI model to respond more accurately, enabling it to quickly and accurately generate legal documents that meet the user's requirements.

[0513] As such, the system is designed to enable users to easily generate legal documents and receive legal advice quickly and efficiently.

[0514] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0515] Step 1:

[0516] A user accesses the system from a terminal and logs in. Specifically, the user uses a smartphone, tablet, or computer to launch a browser or a dedicated application. They enter their username and password on the system's login screen and click the "Login" button. The server checks the entered authentication information against the database, and if authentication is successful, displays the dashboard screen to the user. The input is the username and password, and the output is a login success message or the dashboard screen.

[0517] Step 2:

[0518] The user inputs their legal consultation by voice or text. Specifically, the user clicks the microphone icon to switch to voice input mode and speaks into the microphone, saying "I would like to create an employment contract," or types "I would like to create an employment contract" into the text box and submits it. The input is voice data or text data, and the output is a screen displaying the content of the legal consultation.

[0519] Step 3:

[0520] The device converts the voice data into text data. The device calls the Google Cloud Speech-to-Text API and sends the voice data acquired from the microphone. The API converts the voice data into text data, and the device receives the converted text. The converted text data is sent to the server. The input is voice data, and the output is text data.

[0521] Step 4:

[0522] The server analyzes the text data. The server passes the received text data to a natural language processing engine (e.g., the BERT model), which analyzes the text and extracts key keywords and phrases. Specifically, it extracts keywords related to "creating an employment contract" and understands the user's intent. The input is text data, and the output is the keywords extracted as a result of the analysis.

[0523] Step 5:

[0524] The server generates legal advice and provides it to the user. The server searches for relevant legal information from a legal database and generates advice appropriate to the user's consultation. The generated advice is sent in text format to the terminal and displayed to the user. Specifically, it displays the message, "Employment contracts must include items such as job description, salary, and working hours." The input is keywords from the analysis results, and the output is the legal advice text.

[0525] Step 6:

[0526] The server selects a document template and automatically fills in the user's information. When the user selects "Generate Document," the server selects an appropriate employment contract template from the DocuSign template library. The server automatically fills in information based on the user's consultation details into the template. Specifically, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template. The input is the text of the legal advice, and the output is the generated document draft.

[0527] Step 7:

[0528] The user checks the generated document and gives instructions for corrections. The generated document is displayed on the user's device, and the user checks the contents. If corrections are necessary, the user clicks on the relevant section and gives instructions for corrections in text or voice. Specifically, the user might instruct, "I want my salary changed to 350,000 yen per month." The server receives the instructions, corrects the document again, and generates it. The input is the user's correction instructions, and the output is the corrected document.

[0529] Step 8:

[0530] The server saves the final document and outputs it as needed. After the user has finalized the document, the server saves it in PDF format as instructed. If necessary, it applies an electronic signature and sends the completed document to the email address specified by the user. Specifically, the completed employment contract is emailed to the new employee. The input is the finalized document, and the output is the saved PDF file and a transmission completion message.

[0531] (Application example 1)

[0532] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0533] Conventional legal document generation systems are often based on simple voice or text input, which can lead to long wait times in physical stores and make it difficult to receive reliable advice online. Furthermore, generating and editing legal documents places a heavy burden on users, making it difficult to provide appropriate legal support, especially in virtual stores.

[0534] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0535] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data to generate legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for providing legal advice within the virtual store, and means for accepting input via smart glasses or a smartphone. This enables users to easily and quickly receive appropriate legal advice even within the virtual store and efficiently generate high-quality legal documents.

[0536] The "means for accepting legal consultation input from the user" is an interface that allows the user to input legal questions or inquiries to the system.

[0537] "Means for converting to text using voice recognition technology" refers to technology for converting voice data entered by a user into text data.

[0538] The "means for analyzing the converted text data and generating legal advice" is a technology that analyzes the text data using natural language processing and generates appropriate legal advice based on the analysis.

[0539] The "means for providing the generated legal advice to the user" is a method for providing the generated legal advice to the user in an easy-to-view format.

[0540] The "means for selecting a legal document template" is a method for automatically selecting an appropriate legal document template based on the content of the user's consultation.

[0541] The "means for automatically inputting information based on the content of a user's conversation into a template" is a technology for automatically inputting information obtained from the content of a user's consultation into a selected template.

[0542] "Means for displaying the generated document to the user and regenerating it based on correction instructions" refers to a technology for displaying the generated document so that the user can check it, and regenerating the document based on the user's correction instructions.

[0543] "Means for saving and outputting the final document" refers to a function for saving the document that has been finally confirmed by the user and outputting it in a format such as printing or generating a PDF as necessary.

[0544] A "means for providing legal advice within a virtual store" is a technology for providing legal advice to a user within a virtual reality environment.

[0545] "Means for accepting input via smart glasses or a smartphone" refers to a method for accepting input from a user using smart glasses or a smartphone.

[0546] This invention is a system for accepting legal consultations from users and generating legal documents quickly and accurately. The system is composed of multiple components, each of which fulfills a specific role.

[0547] First, users access the system using smart glasses or a smartphone and log in by entering their authentication information. Next, users can input legal inquiries by voice or text. For example, they can make specific inquiries such as "I would like to create a rental contract for a store."

[0548] The system converts input voice data into text data using speech recognition technology. This technology is realized, for example, using the speech_recognition module. The converted text data is sent to a server and analyzed using a natural language processing engine (e.g., spaCy). This allows the system to understand the content of the user's legal consultation and generate appropriate legal advice.

[0549] The generated legal advice is then provided to the user via smart glasses or a smartphone, with specific advice such as "The rental agreement must include information such as rent, contract duration, and responsibility for repairs."

[0550] Next, when a user requests the generation of a document, the server automatically selects an appropriate template from a database of legal document templates and automatically populates the template with information based on the user's conversation. This process is performed using, for example, the python-docx module.

[0551] The generated document is displayed to the user, who can check the document contents through smart glasses or a smartphone. If necessary, the user can provide correction instructions, and the server will regenerate the document based on those instructions. After the regenerated document has received final confirmation, it can be digitally signed, saved, printed, or otherwise manipulated. The completed document is saved in PDF format and sent to a designated person.

[0552] For example, if a user asks "I want to create a rental contract for a store," the prompt might look like this:

[0553] Prompt statement:

[0554] "I would like to request a store rental agreement."

[0555] From such prompts, the system can automatically select a rental agreement template and automatically enter the necessary information based on the user's input, generating a high-quality document.

[0556] As described above, the system of the present invention allows users to easily receive legal advice and efficiently generate legal documents within a virtual storefront.

[0557] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0558] Step 1:

[0559] A user accesses the system using smart glasses or a smartphone and enters authentication information to log in. The entered authentication information consists of a username and password, which the system receives and performs an authentication process to establish a logged-in state.

[0560] Input: Username, Password

[0561] Output: Notification of successful or failed login

[0562] Step 2:

[0563] The user inputs legal advice by voice or text. The user can use the microphone on their smart glasses or smartphone to input voice, or use the keyboard to input text. For example, the user can input "I would like to create a rental agreement for a store."

[0564] Input: Audio or text data

[0565] Output: Text data of legal consultation content

[0566] Step 3:

[0567] When the terminal receives voice input, it converts the voice data into text data using voice recognition technology, such as the speech_recognition module, and sends the converted text data to the server.

[0568] Input: Audio data

[0569] Output: Text data

[0570] Step 4:

[0571] The server analyzes the received text data using a natural language processing engine (e.g., spaCy). Specifically, it extracts the legal consultation content from the text data and understands the related information.

[0572] Input: Text data

[0573] Output: Analysis results (legal advice)

[0574] Step 5:

[0575] The server searches for appropriate advice from a legal knowledge base and provides the generated legal advice to the user, such as "The rental agreement must include information such as rent, contract period, and responsibility for repairs."

[0576] Input: Analysis results

[0577] Output: Legal advice

[0578] Step 6:

[0579] When a user requests the generation of a document, the server automatically selects an appropriate template from a legal document template database and automatically inputs information based on the user's conversation into the template. For example, specific information such as "rent: 120,000 yen, contract period: 1 year" can be input.

[0580] Input: User's document generation request, analysis results

[0581] Output: Auto-filled template

[0582] Step 7:

[0583] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can provide instructions for correction, and the server will regenerate the document based on those instructions.

[0584] Input: Auto-filled template, user correction instructions

[0585] Output: The corrected document

[0586] Step 8:

[0587] The finalized document is saved, digitally signed, printed, or output as a PDF, as needed, and the completed document is sent to a designated person.

[0588] Input: Finalized document

[0589] Output: Saved document, PDF file, email

[0590] Through these steps, users can easily and quickly receive legal advice and efficiently generate high-quality legal documents.

[0591] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0592] The system of the present invention is an integrated legal support system that not only receives legal consultations from users, provides legal advice based on the consultations, and generates legal documents, but also recognizes the user's emotions and responds accordingly. This system is realized by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions.

[0593] Embodiments of the invention

[0594] 1. A user accesses the system

[0595] A user accesses the system's application using a device (e.g., smartphone, tablet, computer), enters authentication information (user name and password) on the login screen, and logs in to the system.

[0596] 2. Legal consultation via voice or text input

[0597] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their legal advice by text. For example, if a user says, "I would like to create an employment contract," this information is entered into the system.

[0598] 3. Speech Recognition and Text Conversion

[0599] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[0600] 4. Text Analysis Using Natural Language Processing

[0601] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[0602] 5. Analysis of user emotions using an emotion recognition engine

[0603] The server uses an emotion engine to analyze the user's emotions based on the user's voice data and text data. For example, if the user is feeling nervous or anxious, the emotion engine will recognize this.

[0604] 6. Providing legal advice

[0605] The server generates appropriate legal advice based on the user's legal consultation content and emotional state and sends it to the terminal. The terminal then displays the generated advice to the user. For example, the advice provided may include "job description, salary, and working hours in the employment contract."

[0606] 7. Document template selection and auto-fill

[0607] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[0608] 8. Viewing and Modifying Documents

[0609] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[0610] 9. Save and print the final document

[0611] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[0612] In this way, by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions, the system can quickly and efficiently assist users in creating legal documents and generate high-quality legal documents that take the user's emotions into consideration.

[0613] The processing flow will be explained below.

[0614] Step 1:

[0615] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (user name and password) on the login screen.

[0616] Step 2:

[0617] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[0618] Step 3:

[0619] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[0620] Step 4:

[0621] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[0622] Step 5:

[0623] The server uses an emotion recognition engine to analyze the user's emotions. The server analyzes the user's emotions based on voice and text data. For example, it recognizes emotions such as "I'm in a hurry" or "I'm anxious."

[0624] Step 6:

[0625] The server generates legal advice and sends it to the terminal. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the terminal. The terminal displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours." It takes the user's feelings into consideration and uses gentle language or provides brief explanations if the user is in a hurry.

[0626] Step 7:

[0627] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[0628] Step 8:

[0629] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[0630] Step 9:

[0631] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[0632] Step 10:

[0633] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[0634] Step 11:

[0635] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[0636] Step 12:

[0637] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[0638] Step 13:

[0639] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[0640] Step 14:

[0641] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[0642] In this way, the system supports users in creating legal documents quickly and efficiently, and enables the generation of high-quality legal documents that also take the user's feelings into consideration.

[0643] Example 2

[0644] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0645] Conventional legal support systems have difficulty not only accurately analyzing the consultation content provided by users and generating appropriate legal advice, but also responding while taking the user's emotions into consideration. Furthermore, the accuracy and efficiency of the generated legal documents are insufficient, and users have to spend a lot of time reviewing and revising the documents. Furthermore, few systems support both voice input and keyboard input, which reduces user convenience. There is a need to provide an integrated system that can solve these issues and provide users with high-quality, prompt legal support.

[0646] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for accepting legal consultation input from a user; means for converting the input into text using speech recognition technology; means for analyzing the converted text data using a natural language processing engine to generate legal advice; means for determining the user's emotional state based on the analyzed text data and an emotion recognition engine; means for providing the generated legal advice to the user; means for selecting a legal document template in response to the user's document generation request; means for automatically inputting information based on the user's conversation content into the selected template; means for displaying the generated document to the user and regenerating it based on correction instructions; and means for saving and outputting the final document. This makes it possible to respond to various input methods from users and quickly provide high-quality legal support that takes their emotional state into consideration.

[0647] The "means for accepting input of legal consultation from the user" is a means for receiving the content of the consultation when the user makes a legal consultation to the system.

[0648] "Means for converting to text using speech recognition technology" refers to means that use technology to convert voice data uttered by a user into text data.

[0649] The "means for generating legal advice by analyzing using a natural language processing engine" is a means for generating legal advice based on the content of the user's consultation using a natural language processing engine that analyzes text data.

[0650] "Means for determining the emotional state of a user based on an emotion recognition engine" refers to means for determining the emotional state of a user (e.g., tension, anxiety, relief) using an emotion recognition engine based on the user's voice or text data.

[0651] The "means for providing generated legal advice to a user" refers to a means for conveying generated legal advice to a user.

[0652] The "means for selecting a legal document template" is a means for selecting, from a database, a legal document template that is suitable for a user's document generation request.

[0653] The "means for automatically inputting information based on the content of the user's conversation" is a means for automatically inputting information based on the content of the user's consultation or request into a selected template.

[0654] The "means for displaying the generated document to the user and regenerating it based on a correction instruction" refers to a means for displaying the generated document to the user and regenerating the document based on a correction instruction from the user.

[0655] The "means for saving and outputting the final document" refers to the means for digitally signing, saving, printing, emailing, etc. the final document.

[0656] This invention relates to an integrated legal support system that not only receives legal consultation input from users, provides legal advice based on that input, and generates legal documents, but also recognizes the user's emotions and responds appropriately. Specifically, this system is realized by combining voice recognition technology, a natural language processing engine, an emotion recognition engine, and an automatic document generation function.

[0657] The hardware required to implement this system includes the user's device (e.g., smartphone, tablet, computer) and server. The software uses speech recognition technology (e.g., Google Cloud Speech-to-Text), natural language processing engines (e.g., spaCy, BERT), emotion recognition engines (e.g., IBM Watson Tone Analyzer), and automatic document generation functions.

[0658] System Operation Overview

[0659] 1. A user accesses the system

[0660] A user accesses the system's application using a smartphone, tablet, or computer and enters their credentials on the login screen. The server validates the information and redirects the user to the main menu screen.

[0661] 2. Legal consultation via voice or text input

[0662] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their consultation details in text. For example, if a user says, "I would like to create an employment contract," that information is entered into the system.

[0663] 3. Speech Recognition and Text Conversion

[0664] The device captures the user's voice and converts it to text using Google Cloud Speech-to-Text, which is then sent to a server.

[0665] 4. Text Analysis Using Natural Language Processing

[0666] The server analyzes the received text data using a natural language processing engine (e.g., spaCy, BERT) and generates legal advice by extracting relevant information based on the user's input (e.g., "Create an employment contract").

[0667] 5. Analysis of user emotions using an emotion recognition engine

[0668] The server inputs voice and text data into IBM Watson Tone Analyzer, which analyzes the user's emotional state (e.g., "tension" or "anxiety").

[0669] 6. Providing legal advice

[0670] The server generates legal advice based on the analysis results and sends it to the device, which then displays it to the user. For example, the advice might be, "Employment contracts must include job descriptions, salary, and working hours."

[0671] 7. Document template selection and auto-fill

[0672] When a user requests the generation of a legal document, the server selects an appropriate template and automatically inputs the user's conversation content (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") into that template.

[0673] 8. Viewing and Modifying Documents

[0674] The generated document is displayed on the terminal, and the user can check the contents. If necessary, they can provide instructions for correction, and the server will regenerate the document based on those instructions.

[0675] 9. Save and print the final document

[0676] The user performs a final check and then saves the completed document, digitally signs it, prints it, sends it by email, etc. The server executes these operations and saves the final version of the document.

[0677] Specific examples

[0678] For example, by entering the following prompt, the system can efficiently generate legal documents based on the user's needs:

[0679] "I would like to create an employment contract. I would like to be employed as an engineer with a monthly salary of 300,000 yen."

[0680] This prompt allows users to easily create the necessary legal documents and receive appropriate legal advice.

[0681] As described above, this system integrates voice recognition technology, a natural language processing engine, an emotion recognition engine, and automatic document generation functions, enabling it to provide users with high-quality, efficient legal support.

[0682] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0683] Step 1: User accesses the system

[0684] Input: A user accesses the system's application using a smartphone, tablet, or computer and enters their username and password on the login screen.

[0685] Specific operation: The authentication information entered by the user is sent to the server via the terminal.

[0686] Data processing: The server checks the authentication information against a database to verify whether the user has a valid account.

[0687] Output: If the validation is successful, the server redirects the user to the main menu screen.

[0688] Step 2: Legal consultation via voice or text

[0689] Input: The user selects the "Legal Consultation" option on the main menu screen and then either uses the microphone to speak or uses the keyboard to enter text.

[0690] Specific behavior: The user speaks "I would like to create an employment contract" or types "I would like to create an employment contract" in text.

[0691] Output: The audio or text data is saved to the device.

[0692] Step 3: Speech recognition and text conversion

[0693] Input: Audio data stored on the device.

[0694] Specific operation: The device uses voice recognition technology (e.g., Google Cloud Speech-to-Text) to convert voice data into text data.

[0695] Data Processing: The process of analyzing the audio data and converting it into corresponding text takes place.

[0696] Output: The converted text data (e.g., "I would like to create an employment contract") is sent to the server.

[0697] Step 4: Text analysis using natural language processing

[0698] Input: The text data sent to the server.

[0699] Specific operation: The server analyzes the received text data using a natural language processing (NLP) engine (e.g., spaCy, BERT).

[0700] Data processing: Extract the user's inquiry content (e.g., "drafting an employment contract") from the text data and search for related legal information.

[0701] Output: Legal advice data based on the analysis results.

[0702] Step 5: Analyze user emotions using an emotion recognition engine

[0703] Input: Audio and text data.

[0704] Specific operation: The server inputs the voice data and text data into an emotion recognition engine (e.g., IBM Watson Tone Analyzer).

[0705] Data processing: Analyze the user's emotional state (e.g., "tension" or "anxiety") from the input data and assign an emotional tag.

[0706] Output: User's emotional state data.

[0707] Step 6: Providing legal advice

[0708] Input: Analysis results of the natural language processing engine and the emotion recognition engine.

[0709] Specific behavior: The server generates appropriate legal advice based on these results.

[0710] Data processing: The generated legal advice is customized to take into account the user's emotional state.

[0711] Output: Customized legal advice is sent to the terminal, which displays it to the user, for example, "Employment contracts must include job descriptions, salary, and working hours."

[0712] Step 7: Select a document template and auto-fill

[0713] Input: The user's document generation request.

[0714] Specific operation: The server selects a template suitable for the user's request from a database of legal document templates.

[0715] Data processing: The content of the user's conversation (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") is automatically entered into the selected template.

[0716] Output: Completed auto-filled legal document template data.

[0717] Step 8: View and modify the document

[0718] Input: Auto-filled legal document template data.

[0719] Specific operation: The generated document is displayed on the terminal and the user checks the contents.

[0720] Data processing: The user inputs correction instructions as needed, which are then sent to the server.

[0721] Output: Document data that reflects the user's correction instructions.

[0722] Step 9: Save and print the final document

[0723] Input: The corrected document data.

[0724] Specific actions: The user performs a final review and specifies actions such as saving the completed document, digitally signing it, printing it, or sending it by email.

[0725] Data processing: The server generates a document in the specified format (e.g., PDF) and sends the data to the specified storage or destination.

[0726] Output: The final legal document data is saved and sent as needed.

[0727] (Application example 2)

[0728] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0729] Conventional legal consultation systems can accept legal consultations from users, perform speech recognition and text analysis, and provide legal advice, but they have the problem of being unable to respond to the user's emotions. Even when a user is feeling anxious or nervous, conventional systems are unable to recognize and respond to those emotions, creating a need for improved user experience. Furthermore, when it comes to generating legal documents, simply selecting a template and automatically entering information is not enough; a more user-friendly system that adapts to the user's emotional state is also needed.

[0730] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0731] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for analyzing the user's emotions, means for adjusting a response based on the analyzed emotions, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, and means for saving and outputting the final document, thereby enabling optimal legal advice and document generation according to the user's emotional state.

[0732] "Legal consultation input" refers to the act of a user speaking to or inputting information about a legal problem or question into the system, and the content of that information.

[0733] "Speech recognition technology" is a technology that converts voice data into text data.

[0734] "Text data" refers to text information converted using voice recognition technology.

[0735] "Legal Advice" means professional opinions and suggestions provided based on a User's legal consultation input.

[0736] "Emotion analysis" is a technology that reads emotions from a user's voice data or text data and classifies those emotions.

[0737] "Adjusting response" refers to changing the legal advice provided or the way in which a conversation is conducted based on the analyzed user's emotions.

[0738] A "document generation request" refers to a user requesting the system to generate a specific legal document.

[0739] "Legal Document Template" refers to a template for creating a specific legal document.

[0740] "Auto-filling information" refers to automatically filling in required information into a selected template based on the user's input.

[0741] "Modification instructions" refer to instructions that a user requests to change a generated document.

[0742] "Final Document" refers to the completed legal document after user review and correction.

[0743] "Storing and outputting" refers to storing the final document in digital form and providing it to the user, such as by physically printing it, if necessary.

[0744] System configuration

[0745] The system according to the present invention comprises the following hardware and software. The hardware includes a device (such as a smartphone or a head-mounted display (HMD)) and a microphone for the user to receive legal consultation. The software includes speech recognition technology, an emotion analysis engine, a natural language processing engine, and an automatic document generation function.

[0746] Program Overview

[0747] 1. Speech Recognition Technology

[0748] The device receives voice input from the user and converts the voice data into text data using voice recognition technology (e.g., Python's speech_recognition library).

[0749] 2. Natural Language Processing

[0750] The server analyzes the converted text data using a natural language processing engine (e.g., NLPProcessor) and generates legal advice based on the legal consultation content.

[0751] 3. Emotion analysis

[0752] The server analyzes the user's emotions from the voice and text data using an emotion analysis engine (e.g., EmotionRecognizer). Based on the analyzed emotion data, the system adjusts the content of the legal advice and documents it generates.

[0753] 4. Generating Legal Documents

[0754] In response to a user's document generation request, the server selects a legal document template (e.g., LegalDocumentGenerator) and automatically fills in information based on the user's conversation.

[0755] 5. Viewing and Modifying Documents

[0756] The generated document is displayed to the user, and if the user requests corrections, it is regenerated. By repeating this process, the final document is completed.

[0757] 6. Saving and printing the final document

[0758] After the final confirmation, the document is digitally signed, saved, printed, etc. based on the user's instructions. The completed document is saved in PDF format and provided to the user.

[0759] Specific examples

[0760] When a user uses their smartphone to voice-input "I want to create a divorce agreement," the system converts the speech into text. The natural language processing engine then analyzes the text and generates the legal advice the user is seeking. At the same time, the sentiment analysis engine analyzes the user's emotions and, if it determines that the user is feeling anxious, makes suggestions to alleviate the user's anxiety.

[0761] An example of a prompt for a generative AI model is:

[0762] User Input:

[0763] I want to create a divorce agreement

[0764] Please tell me the details of the division of assets

[0765] Generated AI prompt:

[0766] "User wants to create divorce agreement. Feeling uneasy. Please provide appropriate legal advice and how to generate the document. Please include example sentences."

[0767] As in this example, the system can accept legal consultations from users, provide appropriate legal advice in real time, respond to their emotions, and generate, save, and output the final legal documents.

[0768] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0769] Step 1:

[0770] The user inputs the consultation details into the terminal by voice or text.

[0771] Input: The user speaks using a microphone or enters text using a keyboard.

[0772] Processing: The device uses voice recognition technology to convert the voice data into text data. If the input is text, it is treated as text data.

[0773] Output: Sent to the server as text data.

[0774] Step 2:

[0775] The server receives the text data and analyzes it using a natural language processing engine.

[0776] Input: Text data sent from the terminal.

[0777] Processing: The server's natural language processing engine analyzes the text data and extracts the user's legal consultation details.

[0778] Output: Extracted legal consultation content.

[0779] Step 3:

[0780] The server analyzes the user's emotions and obtains the results.

[0781] Input: User voice and text data.

[0782] Processing: The server's emotion analysis engine analyzes the audio and text data to recognize emotional states (e.g., anxiety, tension).

[0783] Output: Emotion analysis results.

[0784] Step 4:

[0785] The server generates appropriate legal advice based on the content of the legal consultation and the results of sentiment analysis.

[0786] Input: Legal consultation content and sentiment analysis results.

[0787] Processing: A natural language processing engine integrates legal consultation content with sentiment analysis results to generate tailored legal advice for the user.

[0788] Output: The generated legal advice.

[0789] Step 5:

[0790] The server transmits legal advice to the terminal and provides it to the user.

[0791] Input: The generated legal advice.

[0792] Processing: The server sends the legal advice to the device, which displays it to the user.

[0793] Output: The legal advice that is displayed to the user.

[0794] Step 6:

[0795] The user makes a document generation request.

[0796] Input: The user's document generation request.

[0797] Process: The user sends a document generation request to the server through the terminal.

[0798] Output: A request to the server to generate the document.

[0799] Step 7:

[0800] The server selects the appropriate legal document template and auto-fills the information.

[0801] Input: Document generation request and user consultation.

[0802] Processing: The server selects an appropriate template from a legal document template database and automatically fills in information based on the user's conversation.

[0803] Output: The generated legal document.

[0804] Step 8:

[0805] The server sends the generated document to the terminal and displays it to the user.

[0806] Input: The generated legal document.

[0807] Process: The server sends the document to the terminal, which displays it to the user.

[0808] Output: The document that is displayed to the user.

[0809] Step 9:

[0810] The user checks the document and gives instructions for corrections as necessary.

[0811] Input: The user checks the displayed document and gives instructions for correction if necessary.

[0812] Processing: The server regenerates the document based on the user's correction instructions.

[0813] Output: The corrected document.

[0814] Step 10:

[0815] The server stores and outputs the final document.

[0816] Input: Final revised document.

[0817] Processing: The server stores the final document digitally and prints or emails it as needed.

[0818] Output: storing in digital form or providing to users.

[0819] The above steps enable optimal legal advice and document generation according to the user's emotional state.

[0820] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0821] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0822] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0823] [Third embodiment]

[0824] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0825] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0826] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0827] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0828] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0829] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0830] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0831] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0832] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0833] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0834] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0835] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0836] The system of the present invention is an integrated legal support system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system aims to accept legal consultations from users and generate legal documents quickly and accurately based on the consultations.

[0837] Embodiments of the invention

[0838] 1. A user accesses the system

[0839] A user accesses an application in the system using a device (e.g., a smartphone, tablet, or computer). The user enters authentication information (user name and password) on the login screen to log in to the system.

[0840] 2. Legal consultation via voice or text input

[0841] Users can use a microphone to give legal advice by voice, or they can use a keyboard to input their consultation details in text. For example, if a user says, "I want to create an employment contract," this information is entered into the system.

[0842] 3. Speech Recognition and Text Conversion

[0843] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[0844] 4. Text Analysis Using Natural Language Processing

[0845] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[0846] 5. Providing legal advice

[0847] The server searches for appropriate advice from a legal knowledge base and provides it to the user. The generated advice is displayed to the user via the terminal. For example, the advice provided may be, "Employment contracts must include items such as job description, salary, and working hours."

[0848] 6. Document template selection and auto-fill

[0849] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[0850] 7. Viewing and Modifying Documents

[0851] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[0852] 8. Save and print the final document

[0853] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[0854] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[0855] The processing flow will be explained below.

[0856] Step 1:

[0857] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (username and password) on the login screen.

[0858] Step 2:

[0859] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[0860] Step 3:

[0861] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[0862] Step 4:

[0863] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[0864] Step 5:

[0865] The server generates legal advice and sends it to the device. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the device. The device displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours."

[0866] Step 6:

[0867] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[0868] Step 7:

[0869] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[0870] Step 8:

[0871] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[0872] Step 9:

[0873] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[0874] Step 10:

[0875] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[0876] Step 11:

[0877] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[0878] Step 12:

[0879] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[0880] Step 13:

[0881] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[0882] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[0883] Example 1

[0884] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0885] Currently, many users face the problem of requiring specialized knowledge when preparing legal documents, which is time-consuming and laborious. Furthermore, there are language barriers when seeking legal advice, and there is a lack of systems that support various input methods, including voice input. Therefore, there is a need for an integrated system that allows users to quickly and accurately prepare legal documents and receive expert support.

[0886] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0887] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for using a natural language processing engine to convert speech data, means for using a legal knowledge base for document generation, and means for adding a digital signature to the document and outputting it. This enables users to easily create legal documents and receive quick and accurate legal advice.

[0888] 1. "Legal Consultation Entry" means an entry made by a User seeking advice on a legal question or issue.

[0889] 2. "Speech recognition technology" refers to technology that analyzes input voice data and converts it into corresponding text data.

[0890] 3. "Text data" means text information converted from audio data.

[0891] 4. A "natural language processing engine" is a software engine that analyzes text data and understands its meaning and structure.

[0892] 5. "Legal Advice" refers to information that provides advice or methods for dealing with a user's legal consultation.

[0893] 6. "Template" means a predefined document model that conforms to a specific format.

[0894] 7. "Legal Document" means a formal document required for legal proceedings or contracts.

[0895] 8. A "legal knowledge base" is a database that compiles legal knowledge such as laws, regulations, and precedents.

[0896] 9. "Voice data" means digital information of voice input using a microphone.

[0897] 10. "Correction Instructions" are requests for changes or corrections made by a User to a Generated Document.

[0898] 11. "Digital Signature" means an electronic signature used to ensure the authenticity and integrity of an electronic document.

[0899] 12. "Preservation" means the act of storing generated documents in digital form.

[0900] 13. "Output" means the act of providing a generated document in the form of printing, digital transmission, or other means.

[0901] The legal support system of this invention is an integrated system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system's purpose is to accept legal consultations from users and generate legal documents quickly and accurately based on those consultations.

[0902] First, a user accesses the system from a device such as a smartphone, tablet, or computer, and authenticates by entering a username and password on the login screen. If authentication is successful, the user can access the system's main screen or dashboard.

[0903] Users can use a microphone to voice their legal consultation or a keyboard to input their consultation details. For example, they can input "I would like to create an employment contract." When this input is transmitted to the system, the device converts the voice data into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text API). The converted text data is then sent directly to the server.

[0904] The server analyzes the received text data using a natural language processing engine (e.g., BERT model) to understand the user's inquiry. This analysis extracts important keywords and phrases and identifies the user's intent. The server then searches for appropriate advice from a legal knowledge base (e.g., a statute database) and provides the generated legal advice to the user. The advice is displayed on the device.

[0905] Next, when a user requests the generation of a document, the server selects an appropriate template from a legal document template database (e.g., the DocuSign template library). This template is automatically filled with information based on the user's consultation. For example, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template.

[0906] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can input correction instructions by text or voice. The server receives these instructions and generates the document again.

[0907] After the user has finalized the document, the server saves it as a PDF as instructed, and optionally digitally signs the document and sends the completed document via email, such as an employment contract being emailed to a new employee.

[0908] For example, consider the following prompt:

[0909] "I want to generate an employment contract for an engineer with a monthly salary of 300,000 yen. The main items are job description, salary, and working hours."

[0910] "I want to generate a one-year rental contract. The monthly rent is 50,000 yen and the security deposit is one month's rent."

[0911] Using such prompts allows the generative AI model to respond more accurately, enabling it to quickly and accurately generate legal documents that meet the user's requirements.

[0912] As such, the system is designed to enable users to easily generate legal documents and receive legal advice quickly and efficiently.

[0913] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0914] Step 1:

[0915] A user accesses the system from a terminal and logs in. Specifically, the user uses a smartphone, tablet, or computer to launch a browser or a dedicated application. They enter their username and password on the system's login screen and click the "Login" button. The server checks the entered authentication information against the database, and if authentication is successful, displays the dashboard screen to the user. The input is the username and password, and the output is a login success message or the dashboard screen.

[0916] Step 2:

[0917] The user inputs their legal consultation by voice or text. Specifically, the user clicks the microphone icon to switch to voice input mode and speaks into the microphone, saying "I would like to create an employment contract," or types "I would like to create an employment contract" into the text box and submits it. The input is voice data or text data, and the output is a screen displaying the content of the legal consultation.

[0918] Step 3:

[0919] The device converts the voice data into text data. The device calls the Google Cloud Speech-to-Text API and sends the voice data acquired from the microphone. The API converts the voice data into text data, and the device receives the converted text. The converted text data is sent to the server. The input is voice data, and the output is text data.

[0920] Step 4:

[0921] The server analyzes the text data. The server passes the received text data to a natural language processing engine (e.g., the BERT model), which analyzes the text and extracts key keywords and phrases. Specifically, it extracts keywords related to "creating an employment contract" and understands the user's intent. The input is text data, and the output is the keywords extracted as a result of the analysis.

[0922] Step 5:

[0923] The server generates legal advice and provides it to the user. The server searches for relevant legal information from a legal database and generates advice appropriate to the user's consultation. The generated advice is sent in text format to the terminal and displayed to the user. Specifically, it displays the message, "Employment contracts must include items such as job description, salary, and working hours." The input is keywords from the analysis results, and the output is the legal advice text.

[0924] Step 6:

[0925] The server selects a document template and automatically fills in the user's information. When the user selects "Generate Document," the server selects an appropriate employment contract template from the DocuSign template library. The server automatically fills in information based on the user's consultation details into the template. Specifically, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template. The input is the text of the legal advice, and the output is the generated document draft.

[0926] Step 7:

[0927] The user checks the generated document and gives instructions for corrections. The generated document is displayed on the user's device, and the user checks the contents. If corrections are necessary, the user clicks on the relevant section and gives instructions for corrections in text or voice. Specifically, the user might instruct, "I want my salary changed to 350,000 yen per month." The server receives the instructions, corrects the document again, and generates it. The input is the user's correction instructions, and the output is the corrected document.

[0928] Step 8:

[0929] The server saves the final document and outputs it as needed. After the user has finalized the document, the server saves it in PDF format as instructed. If necessary, it applies an electronic signature and sends the completed document to the email address specified by the user. Specifically, the completed employment contract is emailed to the new employee. The input is the finalized document, and the output is the saved PDF file and a transmission completion message.

[0930] (Application example 1)

[0931] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0932] Conventional legal document generation systems are often based on simple voice or text input, which can lead to long wait times in physical stores and make it difficult to receive reliable advice online. Furthermore, generating and editing legal documents places a heavy burden on users, making it difficult to provide appropriate legal support, especially in virtual stores.

[0933] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0934] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data to generate legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for providing legal advice within the virtual store, and means for accepting input via smart glasses or a smartphone. This enables users to easily and quickly receive appropriate legal advice even within the virtual store and efficiently generate high-quality legal documents.

[0935] The "means for accepting legal consultation input from the user" is an interface that allows the user to input legal questions or inquiries to the system.

[0936] "Means for converting to text using voice recognition technology" refers to technology for converting voice data entered by a user into text data.

[0937] The "means for analyzing the converted text data and generating legal advice" is a technology that analyzes the text data using natural language processing and generates appropriate legal advice based on the analysis.

[0938] The "means for providing the generated legal advice to the user" is a method for providing the generated legal advice to the user in an easy-to-view format.

[0939] The "means for selecting a legal document template" is a method for automatically selecting an appropriate legal document template based on the content of the user's consultation.

[0940] The "means for automatically inputting information based on the content of a user's conversation into a template" is a technology for automatically inputting information obtained from the content of a user's consultation into a selected template.

[0941] "Means for displaying the generated document to the user and regenerating it based on correction instructions" refers to a technology for displaying the generated document so that the user can check it, and regenerating the document based on the user's correction instructions.

[0942] "Means for saving and outputting the final document" refers to a function for saving the document that has been finally confirmed by the user and outputting it in a format such as printing or generating a PDF as necessary.

[0943] A "means for providing legal advice within a virtual store" is a technology for providing legal advice to a user within a virtual reality environment.

[0944] "Means for accepting input via smart glasses or a smartphone" refers to a method for accepting input from a user using smart glasses or a smartphone.

[0945] This invention is a system for accepting legal consultations from users and generating legal documents quickly and accurately. The system is composed of multiple components, each of which fulfills a specific role.

[0946] First, users access the system using smart glasses or a smartphone and log in by entering their authentication information. Next, users can input legal inquiries by voice or text. For example, they can make specific inquiries such as "I would like to create a rental contract for a store."

[0947] The system converts input voice data into text data using speech recognition technology. This technology is realized, for example, using the speech_recognition module. The converted text data is sent to a server and analyzed using a natural language processing engine (e.g., spaCy). This allows the system to understand the content of the user's legal consultation and generate appropriate legal advice.

[0948] The generated legal advice is then provided to the user via smart glasses or a smartphone, with specific advice such as "The rental agreement must include information such as rent, contract duration, and responsibility for repairs."

[0949] Next, when a user requests the generation of a document, the server automatically selects an appropriate template from a database of legal document templates and automatically populates the template with information based on the user's conversation. This process is performed using, for example, the python-docx module.

[0950] The generated document is displayed to the user, who can check the document contents through smart glasses or a smartphone. If necessary, the user can provide correction instructions, and the server will regenerate the document based on those instructions. After the regenerated document has received final confirmation, it can be digitally signed, saved, printed, or otherwise manipulated. The completed document is saved in PDF format and sent to a designated person.

[0951] For example, if a user asks "I want to create a rental contract for a store," the prompt might look like this:

[0952] Prompt statement:

[0953] "I would like to request a store rental agreement."

[0954] From such prompts, the system can automatically select a rental agreement template and automatically enter the necessary information based on the user's input, generating a high-quality document.

[0955] As described above, the system of the present invention allows users to easily receive legal advice and efficiently generate legal documents within a virtual storefront.

[0956] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0957] Step 1:

[0958] A user accesses the system using smart glasses or a smartphone and enters authentication information to log in. The entered authentication information consists of a username and password, which the system receives and performs an authentication process to establish a logged-in state.

[0959] Input: Username, Password

[0960] Output: Notification of successful or failed login

[0961] Step 2:

[0962] The user inputs legal advice by voice or text. The user can use the microphone on their smart glasses or smartphone to input voice, or use the keyboard to input text. For example, the user can input "I would like to create a rental agreement for a store."

[0963] Input: Audio or text data

[0964] Output: Text data of legal consultation content

[0965] Step 3:

[0966] When the terminal receives voice input, it converts the voice data into text data using voice recognition technology, such as the speech_recognition module, and sends the converted text data to the server.

[0967] Input: Audio data

[0968] Output: Text data

[0969] Step 4:

[0970] The server analyzes the received text data using a natural language processing engine (e.g., spaCy). Specifically, it extracts the legal consultation content from the text data and understands the related information.

[0971] Input: Text data

[0972] Output: Analysis results (legal advice)

[0973] Step 5:

[0974] The server searches for appropriate advice from a legal knowledge base and provides the generated legal advice to the user, such as "The rental agreement must include information such as rent, contract period, and responsibility for repairs."

[0975] Input: Analysis results

[0976] Output: Legal advice

[0977] Step 6:

[0978] When a user requests the generation of a document, the server automatically selects an appropriate template from a legal document template database and automatically inputs information based on the user's conversation into the template. For example, specific information such as "rent: 120,000 yen, contract period: 1 year" can be input.

[0979] Input: User's document generation request, analysis results

[0980] Output: Auto-filled template

[0981] Step 7:

[0982] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can provide instructions for correction, and the server will regenerate the document based on those instructions.

[0983] Input: Auto-filled template, user correction instructions

[0984] Output: The corrected document

[0985] Step 8:

[0986] The finalized document is saved, digitally signed, printed, or output as a PDF, as needed, and the completed document is sent to a designated person.

[0987] Input: Finalized document

[0988] Output: Saved document, PDF file, email

[0989] Through these steps, users can easily and quickly receive legal advice and efficiently generate high-quality legal documents.

[0990] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0991] The system of the present invention is an integrated legal support system that not only receives legal consultations from users, provides legal advice based on the consultations, and generates legal documents, but also recognizes the user's emotions and responds accordingly. This system is realized by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions.

[0992] Embodiments of the invention

[0993] 1. A user accesses the system

[0994] A user accesses the system's application using a device (e.g., smartphone, tablet, computer), enters authentication information (user name and password) on the login screen, and logs in to the system.

[0995] 2. Legal consultation via voice or text input

[0996] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their legal advice by text. For example, if a user says, "I would like to create an employment contract," this information is entered into the system.

[0997] 3. Speech Recognition and Text Conversion

[0998] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[0999] 4. Text Analysis Using Natural Language Processing

[1000] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[1001] 5. Analysis of user emotions using an emotion recognition engine

[1002] The server uses an emotion engine to analyze the user's emotions based on the user's voice data and text data. For example, if the user is feeling nervous or anxious, the emotion engine will recognize this.

[1003] 6. Providing legal advice

[1004] The server generates appropriate legal advice based on the user's legal consultation content and emotional state and sends it to the terminal. The terminal then displays the generated advice to the user. For example, the advice provided may include "job description, salary, and working hours in the employment contract."

[1005] 7. Document template selection and auto-fill

[1006] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[1007] 8. Viewing and Modifying Documents

[1008] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[1009] 9. Save and print the final document

[1010] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[1011] In this way, by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions, the system can quickly and efficiently assist users in creating legal documents and generate high-quality legal documents that take the user's emotions into consideration.

[1012] The processing flow will be explained below.

[1013] Step 1:

[1014] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (user name and password) on the login screen.

[1015] Step 2:

[1016] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[1017] Step 3:

[1018] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[1019] Step 4:

[1020] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[1021] Step 5:

[1022] The server uses an emotion recognition engine to analyze the user's emotions. The server analyzes the user's emotions based on voice and text data. For example, it recognizes emotions such as "I'm in a hurry" or "I'm anxious."

[1023] Step 6:

[1024] The server generates legal advice and sends it to the terminal. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the terminal. The terminal displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours." It takes the user's feelings into consideration and uses gentle language or provides brief explanations if the user is in a hurry.

[1025] Step 7:

[1026] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[1027] Step 8:

[1028] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[1029] Step 9:

[1030] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[1031] Step 10:

[1032] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[1033] Step 11:

[1034] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[1035] Step 12:

[1036] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[1037] Step 13:

[1038] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[1039] Step 14:

[1040] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[1041] In this way, the system supports users in creating legal documents quickly and efficiently, and enables the generation of high-quality legal documents that also take the user's feelings into consideration.

[1042] Example 2

[1043] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1044] Conventional legal support systems have difficulty not only accurately analyzing the consultation content provided by users and generating appropriate legal advice, but also responding while taking the user's emotions into consideration. Furthermore, the accuracy and efficiency of the generated legal documents are insufficient, and users have to spend a lot of time reviewing and revising the documents. Furthermore, few systems support both voice input and keyboard input, which reduces user convenience. There is a need to provide an integrated system that can solve these issues and provide users with high-quality, prompt legal support.

[1045] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for accepting legal consultation input from a user; means for converting the input into text using speech recognition technology; means for analyzing the converted text data using a natural language processing engine to generate legal advice; means for determining the user's emotional state based on the analyzed text data and an emotion recognition engine; means for providing the generated legal advice to the user; means for selecting a legal document template in response to the user's document generation request; means for automatically inputting information based on the user's conversation content into the selected template; means for displaying the generated document to the user and regenerating it based on correction instructions; and means for saving and outputting the final document. This makes it possible to respond to various input methods from users and quickly provide high-quality legal support that takes their emotional state into consideration.

[1046] The "means for accepting input of legal consultation from the user" is a means for receiving the content of the consultation when the user makes a legal consultation to the system.

[1047] "Means for converting to text using speech recognition technology" refers to means that use technology to convert voice data uttered by a user into text data.

[1048] The "means for generating legal advice by analyzing using a natural language processing engine" is a means for generating legal advice based on the content of the user's consultation using a natural language processing engine that analyzes text data.

[1049] "Means for determining the emotional state of a user based on an emotion recognition engine" refers to means for determining the emotional state of a user (e.g., tension, anxiety, relief) using an emotion recognition engine based on the user's voice or text data.

[1050] The "means for providing generated legal advice to a user" refers to a means for conveying generated legal advice to a user.

[1051] The "means for selecting a legal document template" is a means for selecting, from a database, a legal document template that is suitable for a user's document generation request.

[1052] The "means for automatically inputting information based on the content of the user's conversation" is a means for automatically inputting information based on the content of the user's consultation or request into a selected template.

[1053] The "means for displaying the generated document to the user and regenerating it based on a correction instruction" refers to a means for displaying the generated document to the user and regenerating the document based on a correction instruction from the user.

[1054] The "means for saving and outputting the final document" refers to the means for digitally signing, saving, printing, emailing, etc. the final document.

[1055] This invention relates to an integrated legal support system that not only receives legal consultation input from users, provides legal advice based on that input, and generates legal documents, but also recognizes the user's emotions and responds appropriately. Specifically, this system is realized by combining voice recognition technology, a natural language processing engine, an emotion recognition engine, and an automatic document generation function.

[1056] The hardware required to implement this system includes the user's device (e.g., smartphone, tablet, computer) and server. The software uses speech recognition technology (e.g., Google Cloud Speech-to-Text), natural language processing engines (e.g., spaCy, BERT), emotion recognition engines (e.g., IBM Watson Tone Analyzer), and automatic document generation functions.

[1057] System Operation Overview

[1058] 1. A user accesses the system

[1059] A user accesses the system's application using a smartphone, tablet, or computer and enters their credentials on the login screen. The server validates the information and redirects the user to the main menu screen.

[1060] 2. Legal consultation via voice or text input

[1061] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their consultation details in text. For example, if a user says, "I would like to create an employment contract," that information is entered into the system.

[1062] 3. Speech Recognition and Text Conversion

[1063] The device captures the user's voice and converts it to text using Google Cloud Speech-to-Text, which is then sent to a server.

[1064] 4. Text Analysis Using Natural Language Processing

[1065] The server analyzes the received text data using a natural language processing engine (e.g., spaCy, BERT) and generates legal advice by extracting relevant information based on the user's input (e.g., "Create an employment contract").

[1066] 5. Analysis of user emotions using an emotion recognition engine

[1067] The server inputs voice and text data into IBM Watson Tone Analyzer, which analyzes the user's emotional state (e.g., "tension" or "anxiety").

[1068] 6. Providing legal advice

[1069] The server generates legal advice based on the analysis results and sends it to the device, which then displays it to the user. For example, the advice might be, "Employment contracts must include job descriptions, salary, and working hours."

[1070] 7. Document template selection and auto-fill

[1071] When a user requests the generation of a legal document, the server selects an appropriate template and automatically inputs the user's conversation content (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") into that template.

[1072] 8. Viewing and Modifying Documents

[1073] The generated document is displayed on the terminal, and the user can check the contents. If necessary, they can provide instructions for correction, and the server will regenerate the document based on those instructions.

[1074] 9. Save and print the final document

[1075] The user performs a final check and then saves the completed document, digitally signs it, prints it, sends it by email, etc. The server executes these operations and saves the final version of the document.

[1076] Specific examples

[1077] For example, by entering the following prompt, the system can efficiently generate legal documents based on the user's needs:

[1078] "I would like to create an employment contract. I would like to be employed as an engineer with a monthly salary of 300,000 yen."

[1079] This prompt allows users to easily create the necessary legal documents and receive appropriate legal advice.

[1080] As described above, this system integrates voice recognition technology, a natural language processing engine, an emotion recognition engine, and automatic document generation functions, enabling it to provide users with high-quality, efficient legal support.

[1081] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1082] Step 1: User accesses the system

[1083] Input: A user accesses the system's application using a smartphone, tablet, or computer and enters their username and password on the login screen.

[1084] Specific operation: The authentication information entered by the user is sent to the server via the terminal.

[1085] Data processing: The server checks the authentication information against a database to verify whether the user has a valid account.

[1086] Output: If the validation is successful, the server redirects the user to the main menu screen.

[1087] Step 2: Legal consultation via voice or text

[1088] Input: The user selects the "Legal Consultation" option on the main menu screen and then either uses the microphone to speak or uses the keyboard to enter text.

[1089] Specific behavior: The user speaks "I would like to create an employment contract" or types "I would like to create an employment contract" in text.

[1090] Output: The audio or text data is saved to the device.

[1091] Step 3: Speech recognition and text conversion

[1092] Input: Audio data stored on the device.

[1093] Specific operation: The device uses voice recognition technology (e.g., Google Cloud Speech-to-Text) to convert voice data into text data.

[1094] Data Processing: The process of analyzing the audio data and converting it into corresponding text takes place.

[1095] Output: The converted text data (e.g., "I would like to create an employment contract") is sent to the server.

[1096] Step 4: Text analysis using natural language processing

[1097] Input: The text data sent to the server.

[1098] Specific operation: The server analyzes the received text data using a natural language processing (NLP) engine (e.g., spaCy, BERT).

[1099] Data processing: Extract the user's inquiry content (e.g., "drafting an employment contract") from the text data and search for related legal information.

[1100] Output: Legal advice data based on the analysis results.

[1101] Step 5: Analyze user emotions using an emotion recognition engine

[1102] Input: Audio and text data.

[1103] Specific operation: The server inputs the voice data and text data into an emotion recognition engine (e.g., IBM Watson Tone Analyzer).

[1104] Data processing: Analyze the user's emotional state (e.g., "tension" or "anxiety") from the input data and assign an emotional tag.

[1105] Output: User's emotional state data.

[1106] Step 6: Providing legal advice

[1107] Input: Analysis results of the natural language processing engine and the emotion recognition engine.

[1108] Specific behavior: The server generates appropriate legal advice based on these results.

[1109] Data processing: The generated legal advice is customized to take into account the user's emotional state.

[1110] Output: Customized legal advice is sent to the terminal, which displays it to the user, for example, "Employment contracts must include job descriptions, salary, and working hours."

[1111] Step 7: Select a document template and auto-fill

[1112] Input: The user's document generation request.

[1113] Specific operation: The server selects a template suitable for the user's request from a database of legal document templates.

[1114] Data processing: The content of the user's conversation (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") is automatically entered into the selected template.

[1115] Output: Completed auto-filled legal document template data.

[1116] Step 8: View and modify the document

[1117] Input: Auto-filled legal document template data.

[1118] Specific operation: The generated document is displayed on the terminal and the user checks the contents.

[1119] Data processing: The user inputs correction instructions as needed, which are then sent to the server.

[1120] Output: Document data that reflects the user's correction instructions.

[1121] Step 9: Save and print the final document

[1122] Input: The corrected document data.

[1123] Specific actions: The user performs a final review and specifies actions such as saving the completed document, digitally signing it, printing it, or sending it by email.

[1124] Data processing: The server generates a document in the specified format (e.g., PDF) and sends the data to the specified storage or destination.

[1125] Output: The final legal document data is saved and sent as needed.

[1126] (Application example 2)

[1127] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1128] Conventional legal consultation systems can accept legal consultations from users, perform speech recognition and text analysis, and provide legal advice, but they have the problem of being unable to respond to the user's emotions. Even when a user is feeling anxious or nervous, conventional systems are unable to recognize and respond to those emotions, creating a need for improved user experience. Furthermore, when it comes to generating legal documents, simply selecting a template and automatically entering information is not enough; a more user-friendly system that adapts to the user's emotional state is also needed.

[1129] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1130] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for analyzing the user's emotions, means for adjusting a response based on the analyzed emotions, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, and means for saving and outputting the final document, thereby enabling optimal legal advice and document generation according to the user's emotional state.

[1131] "Legal consultation input" refers to the act of a user speaking to or inputting information about a legal problem or question into the system, and the content of that information.

[1132] "Speech recognition technology" is a technology that converts voice data into text data.

[1133] "Text data" refers to text information converted using voice recognition technology.

[1134] "Legal Advice" means professional opinions and suggestions provided based on a User's legal consultation input.

[1135] "Emotion analysis" is a technology that reads emotions from a user's voice data or text data and classifies those emotions.

[1136] "Adjusting response" refers to changing the legal advice provided or the way in which a conversation is conducted based on the analyzed user's emotions.

[1137] A "document generation request" refers to a user requesting the system to generate a specific legal document.

[1138] "Legal Document Template" refers to a template for creating a specific legal document.

[1139] "Auto-filling information" refers to automatically filling in required information into a selected template based on the user's input.

[1140] "Modification instructions" refer to instructions that a user requests to change a generated document.

[1141] "Final Document" refers to the completed legal document after user review and correction.

[1142] "Storing and outputting" refers to storing the final document in digital form and providing it to the user, such as by physically printing it, if necessary.

[1143] System configuration

[1144] The system according to the present invention comprises the following hardware and software. The hardware includes a device (such as a smartphone or a head-mounted display (HMD)) and a microphone for the user to receive legal consultation. The software includes speech recognition technology, an emotion analysis engine, a natural language processing engine, and an automatic document generation function.

[1145] Program Overview

[1146] 1. Speech Recognition Technology

[1147] The device receives voice input from the user and converts the voice data into text data using voice recognition technology (e.g., Python's speech_recognition library).

[1148] 2. Natural Language Processing

[1149] The server analyzes the converted text data using a natural language processing engine (e.g., NLPProcessor) and generates legal advice based on the legal consultation content.

[1150] 3. Emotion analysis

[1151] The server analyzes the user's emotions from the voice and text data using an emotion analysis engine (e.g., EmotionRecognizer). Based on the analyzed emotion data, the system adjusts the content of the legal advice and documents it generates.

[1152] 4. Generating Legal Documents

[1153] In response to a user's document generation request, the server selects a legal document template (e.g., LegalDocumentGenerator) and automatically fills in information based on the user's conversation.

[1154] 5. Viewing and Modifying Documents

[1155] The generated document is displayed to the user, and if the user requests corrections, it is regenerated. By repeating this process, the final document is completed.

[1156] 6. Saving and printing the final document

[1157] After the final confirmation, the document is digitally signed, saved, printed, etc. based on the user's instructions. The completed document is saved in PDF format and provided to the user.

[1158] Specific examples

[1159] When a user uses their smartphone to voice-input "I want to create a divorce agreement," the system converts the speech into text. The natural language processing engine then analyzes the text and generates the legal advice the user is seeking. At the same time, the sentiment analysis engine analyzes the user's emotions and, if it determines that the user is feeling anxious, makes suggestions to alleviate the user's anxiety.

[1160] An example of a prompt for a generative AI model is:

[1161] User Input:

[1162] I want to create a divorce agreement

[1163] Please tell me the details of the division of assets

[1164] Generated AI prompt:

[1165] "User wants to create divorce agreement. Feeling uneasy. Please provide appropriate legal advice and how to generate the document. Please include example sentences."

[1166] As in this example, the system can accept legal consultations from users, provide appropriate legal advice in real time, respond to their emotions, and generate, save, and output the final legal documents.

[1167] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1168] Step 1:

[1169] The user inputs the consultation details into the terminal by voice or text.

[1170] Input: The user speaks using a microphone or enters text using a keyboard.

[1171] Processing: The device uses voice recognition technology to convert the voice data into text data. If the input is text, it is treated as text data.

[1172] Output: Sent to the server as text data.

[1173] Step 2:

[1174] The server receives the text data and analyzes it using a natural language processing engine.

[1175] Input: Text data sent from the terminal.

[1176] Processing: The server's natural language processing engine analyzes the text data and extracts the user's legal consultation details.

[1177] Output: Extracted legal consultation content.

[1178] Step 3:

[1179] The server analyzes the user's emotions and obtains the results.

[1180] Input: User voice and text data.

[1181] Processing: The server's emotion analysis engine analyzes the audio and text data to recognize emotional states (e.g., anxiety, tension).

[1182] Output: Emotion analysis results.

[1183] Step 4:

[1184] The server generates appropriate legal advice based on the content of the legal consultation and the results of sentiment analysis.

[1185] Input: Legal consultation content and sentiment analysis results.

[1186] Processing: A natural language processing engine integrates legal consultation content with sentiment analysis results to generate tailored legal advice for the user.

[1187] Output: The generated legal advice.

[1188] Step 5:

[1189] The server transmits legal advice to the terminal and provides it to the user.

[1190] Input: The generated legal advice.

[1191] Processing: The server sends the legal advice to the device, which displays it to the user.

[1192] Output: The legal advice that is displayed to the user.

[1193] Step 6:

[1194] The user makes a document generation request.

[1195] Input: The user's document generation request.

[1196] Process: The user sends a document generation request to the server through the terminal.

[1197] Output: A request to the server to generate the document.

[1198] Step 7:

[1199] The server selects the appropriate legal document template and auto-fills the information.

[1200] Input: Document generation request and user consultation.

[1201] Processing: The server selects an appropriate template from a legal document template database and automatically fills in information based on the user's conversation.

[1202] Output: The generated legal document.

[1203] Step 8:

[1204] The server sends the generated document to the terminal and displays it to the user.

[1205] Input: The generated legal document.

[1206] Process: The server sends the document to the terminal, which displays it to the user.

[1207] Output: The document that is displayed to the user.

[1208] Step 9:

[1209] The user checks the document and gives instructions for corrections as necessary.

[1210] Input: The user checks the displayed document and gives instructions for correction if necessary.

[1211] Processing: The server regenerates the document based on the user's correction instructions.

[1212] Output: The corrected document.

[1213] Step 10:

[1214] The server stores and outputs the final document.

[1215] Input: Final revised document.

[1216] Processing: The server stores the final document digitally and prints or emails it as needed.

[1217] Output: storing in digital form or providing to users.

[1218] The above steps enable optimal legal advice and document generation according to the user's emotional state.

[1219] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1220] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1221] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1222] [Fourth embodiment]

[1223] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1224] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1225] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1226] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1227] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1228] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1229] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1230] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1231] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1232] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1233] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1234] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1235] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1236] The system of the present invention is an integrated legal support system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system aims to accept legal consultations from users and generate legal documents quickly and accurately based on the consultations.

[1237] Embodiments of the invention

[1238] 1. A user accesses the system

[1239] A user accesses an application in the system using a device (e.g., a smartphone, tablet, or computer). The user enters authentication information (user name and password) on the login screen to log in to the system.

[1240] 2. Legal consultation via voice or text input

[1241] Users can use a microphone to give legal advice by voice, or they can use a keyboard to input their consultation details in text. For example, if a user says, "I want to create an employment contract," this information is entered into the system.

[1242] 3. Speech Recognition and Text Conversion

[1243] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[1244] 4. Text Analysis Using Natural Language Processing

[1245] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[1246] 5. Providing legal advice

[1247] The server searches for appropriate advice from a legal knowledge base and provides it to the user. The generated advice is displayed to the user via the terminal. For example, the advice provided may be, "Employment contracts must include items such as job description, salary, and working hours."

[1248] 6. Document template selection and auto-fill

[1249] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[1250] 7. Viewing and Modifying Documents

[1251] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[1252] 8. Save and print the final document

[1253] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[1254] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[1255] The processing flow will be explained below.

[1256] Step 1:

[1257] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (username and password) on the login screen.

[1258] Step 2:

[1259] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[1260] Step 3:

[1261] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[1262] Step 4:

[1263] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[1264] Step 5:

[1265] The server generates legal advice and sends it to the device. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the device. The device displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours."

[1266] Step 6:

[1267] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[1268] Step 7:

[1269] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[1270] Step 8:

[1271] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[1272] Step 9:

[1273] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[1274] Step 10:

[1275] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[1276] Step 11:

[1277] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[1278] Step 12:

[1279] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[1280] Step 13:

[1281] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[1282] In this way, the system supports users in creating legal documents quickly and efficiently, enabling even ordinary users to easily create high-quality legal documents.

[1283] Example 1

[1284] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1285] Currently, many users face the problem of requiring specialized knowledge when preparing legal documents, which is time-consuming and laborious. Furthermore, there are language barriers when seeking legal advice, and there is a lack of systems that support various input methods, including voice input. Therefore, there is a need for an integrated system that allows users to quickly and accurately prepare legal documents and receive expert support.

[1286] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1287] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for using a natural language processing engine to convert speech data, means for using a legal knowledge base for document generation, and means for adding a digital signature to the document and outputting it. This enables users to easily create legal documents and receive quick and accurate legal advice.

[1288] 1. "Legal Consultation Entry" means an entry made by a User seeking advice on a legal question or issue.

[1289] 2. "Speech recognition technology" refers to technology that analyzes input voice data and converts it into corresponding text data.

[1290] 3. "Text data" means text information converted from audio data.

[1291] 4. A "natural language processing engine" is a software engine that analyzes text data and understands its meaning and structure.

[1292] 5. "Legal Advice" refers to information that provides advice or methods for dealing with a user's legal consultation.

[1293] 6. "Template" means a predefined document model that conforms to a specific format.

[1294] 7. "Legal Document" means a formal document required for legal proceedings or contracts.

[1295] 8. A "legal knowledge base" is a database that compiles legal knowledge such as laws, regulations, and precedents.

[1296] 9. "Voice data" means digital information of voice input using a microphone.

[1297] 10. "Correction Instructions" are requests for changes or corrections made by a User to a Generated Document.

[1298] 11. "Digital Signature" means an electronic signature used to ensure the authenticity and integrity of an electronic document.

[1299] 12. "Preservation" means the act of storing generated documents in digital form.

[1300] 13. "Output" means the act of providing a generated document in the form of printing, digital transmission, or other means.

[1301] The legal support system of this invention is an integrated system that combines speech recognition technology, natural language processing, and automatic document generation functions. The system's purpose is to accept legal consultations from users and generate legal documents quickly and accurately based on those consultations.

[1302] First, a user accesses the system from a device such as a smartphone, tablet, or computer, and authenticates by entering a username and password on the login screen. If authentication is successful, the user can access the system's main screen or dashboard.

[1303] Users can use a microphone to voice their legal consultation or a keyboard to input their consultation details. For example, they can input "I would like to create an employment contract." When this input is transmitted to the system, the device converts the voice data into text data using voice recognition technology (e.g., Google Cloud Speech-to-Text API). The converted text data is then sent directly to the server.

[1304] The server analyzes the received text data using a natural language processing engine (e.g., BERT model) to understand the user's inquiry. This analysis extracts important keywords and phrases and identifies the user's intent. The server then searches for appropriate advice from a legal knowledge base (e.g., a statute database) and provides the generated legal advice to the user. The advice is displayed on the device.

[1305] Next, when a user requests the generation of a document, the server selects an appropriate template from a legal document template database (e.g., the DocuSign template library). This template is automatically filled with information based on the user's consultation. For example, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template.

[1306] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can input correction instructions by text or voice. The server receives these instructions and generates the document again.

[1307] After the user has finalized the document, the server saves it as a PDF as instructed, and optionally digitally signs the document and sends the completed document via email, such as an employment contract being emailed to a new employee.

[1308] For example, consider the following prompt:

[1309] "I want to generate an employment contract for an engineer with a monthly salary of 300,000 yen. The main items are job description, salary, and working hours."

[1310] "I want to generate a one-year rental contract. The monthly rent is 50,000 yen and the security deposit is one month's rent."

[1311] Using such prompts allows the generative AI model to respond more accurately, enabling it to quickly and accurately generate legal documents that meet the user's requirements.

[1312] As such, the system is designed to enable users to easily generate legal documents and receive legal advice quickly and efficiently.

[1313] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1314] Step 1:

[1315] A user accesses the system from a terminal and logs in. Specifically, the user uses a smartphone, tablet, or computer to launch a browser or a dedicated application. They enter their username and password on the system's login screen and click the "Login" button. The server checks the entered authentication information against the database, and if authentication is successful, displays the dashboard screen to the user. The input is the username and password, and the output is a login success message or the dashboard screen.

[1316] Step 2:

[1317] The user inputs their legal consultation by voice or text. Specifically, the user clicks the microphone icon to switch to voice input mode and speaks into the microphone, saying "I would like to create an employment contract," or types "I would like to create an employment contract" into the text box and submits it. The input is voice data or text data, and the output is a screen displaying the content of the legal consultation.

[1318] Step 3:

[1319] The device converts the voice data into text data. The device calls the Google Cloud Speech-to-Text API and sends the voice data acquired from the microphone. The API converts the voice data into text data, and the device receives the converted text. The converted text data is sent to the server. The input is voice data, and the output is text data.

[1320] Step 4:

[1321] The server analyzes the text data. The server passes the received text data to a natural language processing engine (e.g., the BERT model), which analyzes the text and extracts key keywords and phrases. Specifically, it extracts keywords related to "creating an employment contract" and understands the user's intent. The input is text data, and the output is the keywords extracted as a result of the analysis.

[1322] Step 5:

[1323] The server generates legal advice and provides it to the user. The server searches for relevant legal information from a legal database and generates advice appropriate to the user's consultation. The generated advice is sent in text format to the terminal and displayed to the user. Specifically, it displays the message, "Employment contracts must include items such as job description, salary, and working hours." The input is keywords from the analysis results, and the output is the legal advice text.

[1324] Step 6:

[1325] The server selects a document template and automatically fills in the user's information. When the user selects "Generate Document," the server selects an appropriate employment contract template from the DocuSign template library. The server automatically fills in information based on the user's consultation details into the template. Specifically, information such as "employment as an engineer with a monthly salary of 300,000 yen" is reflected in the template. The input is the text of the legal advice, and the output is the generated document draft.

[1326] Step 7:

[1327] The user checks the generated document and gives instructions for corrections. The generated document is displayed on the user's device, and the user checks the contents. If corrections are necessary, the user clicks on the relevant section and gives instructions for corrections in text or voice. Specifically, the user might instruct, "I want my salary changed to 350,000 yen per month." The server receives the instructions, corrects the document again, and generates it. The input is the user's correction instructions, and the output is the corrected document.

[1328] Step 8:

[1329] The server saves the final document and outputs it as needed. After the user has finalized the document, the server saves it in PDF format as instructed. If necessary, it applies an electronic signature and sends the completed document to the email address specified by the user. Specifically, the completed employment contract is emailed to the new employee. The input is the finalized document, and the output is the saved PDF file and a transmission completion message.

[1330] (Application example 1)

[1331] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1332] Conventional legal document generation systems are often based on simple voice or text input, which can lead to long wait times in physical stores and make it difficult to receive reliable advice online. Furthermore, generating and editing legal documents places a heavy burden on users, making it difficult to provide appropriate legal support, especially in virtual stores.

[1333] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1334] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data to generate legal advice, means for providing the generated legal advice to the user, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, means for saving and outputting the final document, means for providing legal advice within the virtual store, and means for accepting input via smart glasses or a smartphone. This enables users to easily and quickly receive appropriate legal advice even within the virtual store and efficiently generate high-quality legal documents.

[1335] The "means for accepting legal consultation input from the user" is an interface that allows the user to input legal questions or inquiries to the system.

[1336] "Means for converting to text using voice recognition technology" refers to technology for converting voice data entered by a user into text data.

[1337] The "means for analyzing the converted text data and generating legal advice" is a technology that analyzes the text data using natural language processing and generates appropriate legal advice based on the analysis.

[1338] The "means for providing the generated legal advice to the user" is a method for providing the generated legal advice to the user in an easy-to-view format.

[1339] The "means for selecting a legal document template" is a method for automatically selecting an appropriate legal document template based on the content of the user's consultation.

[1340] The "means for automatically inputting information based on the content of a user's conversation into a template" is a technology for automatically inputting information obtained from the content of a user's consultation into a selected template.

[1341] "Means for displaying the generated document to the user and regenerating it based on correction instructions" refers to a technology for displaying the generated document so that the user can check it, and regenerating the document based on the user's correction instructions.

[1342] "Means for saving and outputting the final document" refers to a function for saving the document that has been finally confirmed by the user and outputting it in a format such as printing or generating a PDF as necessary.

[1343] A "means for providing legal advice within a virtual store" is a technology for providing legal advice to a user within a virtual reality environment.

[1344] "Means for accepting input via smart glasses or a smartphone" refers to a method for accepting input from a user using smart glasses or a smartphone.

[1345] This invention is a system for accepting legal consultations from users and generating legal documents quickly and accurately. The system is composed of multiple components, each of which fulfills a specific role.

[1346] First, users access the system using smart glasses or a smartphone and log in by entering their authentication information. Next, users can input legal inquiries by voice or text. For example, they can make specific inquiries such as "I would like to create a rental contract for a store."

[1347] The system converts input voice data into text data using speech recognition technology. This technology is realized, for example, using the speech_recognition module. The converted text data is sent to a server and analyzed using a natural language processing engine (e.g., spaCy). This allows the system to understand the content of the user's legal consultation and generate appropriate legal advice.

[1348] The generated legal advice is then provided to the user via smart glasses or a smartphone, with specific advice such as "The rental agreement must include information such as rent, contract duration, and responsibility for repairs."

[1349] Next, when a user requests the generation of a document, the server automatically selects an appropriate template from a database of legal document templates and automatically populates the template with information based on the user's conversation. This process is performed using, for example, the python-docx module.

[1350] The generated document is displayed to the user, who can check the document contents through smart glasses or a smartphone. If necessary, the user can provide correction instructions, and the server will regenerate the document based on those instructions. After the regenerated document has received final confirmation, it can be digitally signed, saved, printed, or otherwise manipulated. The completed document is saved in PDF format and sent to a designated person.

[1351] For example, if a user asks "I want to create a rental contract for a store," the prompt might look like this:

[1352] Prompt statement:

[1353] "I would like to request a store rental agreement."

[1354] From such prompts, the system can automatically select a rental agreement template and automatically enter the necessary information based on the user's input, generating a high-quality document.

[1355] As described above, the system of the present invention allows users to easily receive legal advice and efficiently generate legal documents within a virtual storefront.

[1356] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1357] Step 1:

[1358] A user accesses the system using smart glasses or a smartphone and enters authentication information to log in. The entered authentication information consists of a username and password, which the system receives and performs an authentication process to establish a logged-in state.

[1359] Input: Username, Password

[1360] Output: Notification of successful or failed login

[1361] Step 2:

[1362] The user inputs legal advice by voice or text. The user can use the microphone on their smart glasses or smartphone to input voice, or use the keyboard to input text. For example, the user can input "I would like to create a rental agreement for a store."

[1363] Input: Audio or text data

[1364] Output: Text data of legal consultation content

[1365] Step 3:

[1366] When the terminal receives voice input, it converts the voice data into text data using voice recognition technology, such as the speech_recognition module, and sends the converted text data to the server.

[1367] Input: Audio data

[1368] Output: Text data

[1369] Step 4:

[1370] The server analyzes the received text data using a natural language processing engine (e.g., spaCy). Specifically, it extracts the legal consultation content from the text data and understands the related information.

[1371] Input: Text data

[1372] Output: Analysis results (legal advice)

[1373] Step 5:

[1374] The server searches for appropriate advice from a legal knowledge base and provides the generated legal advice to the user, such as "The rental agreement must include information such as rent, contract period, and responsibility for repairs."

[1375] Input: Analysis results

[1376] Output: Legal advice

[1377] Step 6:

[1378] When a user requests the generation of a document, the server automatically selects an appropriate template from a legal document template database and automatically inputs information based on the user's conversation into the template. For example, specific information such as "rent: 120,000 yen, contract period: 1 year" can be input.

[1379] Input: User's document generation request, analysis results

[1380] Output: Auto-filled template

[1381] Step 7:

[1382] The generated document is displayed to the user via the terminal, and the user can check the contents. If necessary, the user can provide instructions for correction, and the server will regenerate the document based on those instructions.

[1383] Input: Auto-filled template, user correction instructions

[1384] Output: The corrected document

[1385] Step 8:

[1386] The finalized document is saved, digitally signed, printed, or output as a PDF, as needed, and the completed document is sent to a designated person.

[1387] Input: Finalized document

[1388] Output: Saved document, PDF file, email

[1389] Through these steps, users can easily and quickly receive legal advice and efficiently generate high-quality legal documents.

[1390] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1391] The system of the present invention is an integrated legal support system that not only receives legal consultations from users, provides legal advice based on the consultations, and generates legal documents, but also recognizes the user's emotions and responds accordingly. This system is realized by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions.

[1392] Embodiments of the invention

[1393] 1. A user accesses the system

[1394] A user accesses the system's application using a device (e.g., smartphone, tablet, computer), enters authentication information (user name and password) on the login screen, and logs in to the system.

[1395] 2. Legal consultation via voice or text input

[1396] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their legal advice by text. For example, if a user says, "I would like to create an employment contract," this information is entered into the system.

[1397] 3. Speech Recognition and Text Conversion

[1398] The terminal converts the input voice data into text data using voice recognition technology. The converted text data is then sent to the server as is. For example, a voice message saying "I would like to create an employment contract" is converted into text data saying "I would like to create an employment contract."

[1399] 4. Text Analysis Using Natural Language Processing

[1400] The server analyzes the received text data using a natural language processing engine. As a result of the analysis, it understands the content of the user's consultation. Specifically, the server extracts information related to "drafting an employment contract" and generates appropriate legal advice.

[1401] 5. Analysis of user emotions using an emotion recognition engine

[1402] The server uses an emotion engine to analyze the user's emotions based on the user's voice data and text data. For example, if the user is feeling nervous or anxious, the emotion engine will recognize this.

[1403] 6. Providing legal advice

[1404] The server generates appropriate legal advice based on the user's legal consultation content and emotional state and sends it to the terminal. The terminal then displays the generated advice to the user. For example, the advice provided may include "job description, salary, and working hours in the employment contract."

[1405] 7. Document template selection and auto-fill

[1406] When a user requests the generation of a document, the server selects an appropriate template from a legal document template database. The selected template is automatically filled with information based on the user's conversation. For example, information such as "I will be hired as an engineer with a monthly salary of 300,000 yen" is automatically entered into the template.

[1407] 8. Viewing and Modifying Documents

[1408] The generated document is displayed to the user through the terminal, allowing the user to check the document contents. If necessary, the user can provide instructions for correction, and the server will generate the document again based on those instructions.

[1409] 9. Save and print the final document

[1410] After final review, the document can be digitally signed, saved, printed, etc., based on the user's instructions. For example, a completed employment contract can be saved as a PDF and emailed to the new employee.

[1411] In this way, by combining speech recognition technology, natural language processing, an emotion engine, and automatic document generation functions, the system can quickly and efficiently assist users in creating legal documents and generate high-quality legal documents that take the user's emotions into consideration.

[1412] The processing flow will be explained below.

[1413] Step 1:

[1414] A user accesses the system. The user uses a device (e.g., smartphone, tablet, computer) to log in to the system's application by entering authentication information (user name and password) on the login screen.

[1415] Step 2:

[1416] The user starts a legal consultation. The user enters the content of the consultation by voice using a microphone or by entering text using a keyboard. For example, the user enters "I would like to create an employment contract."

[1417] Step 3:

[1418] The device performs voice recognition. In the case of voice input, the device uses voice recognition technology to convert the voice data into text data. The converted text data is then sent to the server.

[1419] Step 4:

[1420] The server analyzes the text data. The server uses a natural language processing engine to analyze the received text data and understand the legal consultation content of the user (e.g., "drafting an employment contract").

[1421] Step 5:

[1422] The server uses an emotion recognition engine to analyze the user's emotions. The server analyzes the user's emotions based on voice and text data. For example, it recognizes emotions such as "I'm in a hurry" or "I'm anxious."

[1423] Step 6:

[1424] The server generates legal advice and sends it to the terminal. The server searches for appropriate advice from a legal knowledge base and sends the generated advice to the terminal. The terminal displays the advice to the user. For example, it provides advice such as "Employment contracts must include job descriptions, salary, and working hours." It takes the user's feelings into consideration and uses gentle language or provides brief explanations if the user is in a hurry.

[1425] Step 7:

[1426] The user requests document generation. The user requests the system to create a specific document. For example, the user may instruct the system to "create a specific employment contract."

[1427] Step 8:

[1428] The server selects an appropriate template: The server selects an appropriate template (e.g., employment contract template) from a legal document template database according to the user's request.

[1429] Step 9:

[1430] The server extracts the content of the user's conversation and automatically inputs it into a template.The server extracts specific information (e.g., job description, salary, working hours) from the content of the conversation with the user and automatically inputs it into the selected template.

[1431] Step 10:

[1432] The server sends the generated document to the terminal, which displays it to the user. The terminal displays the generated document on the user's screen and asks for confirmation.

[1433] Step 11:

[1434] The user checks the document contents and gives instructions for corrections. The user checks the generated document and gives instructions for any necessary corrections. For example, the user may give instructions such as "I want to change the salary payment method from cash to bank transfer."

[1435] Step 12:

[1436] The server reflects the modifications and regenerates the document. The server modifies the document based on the user's instructions and sends the regenerated document to the terminal.

[1437] Step 13:

[1438] The terminal displays the final document to the user, who then makes a final confirmation. The user then confirms the contents and issues a completion instruction.

[1439] Step 14:

[1440] The server saves and outputs the final document. Based on the user's instructions, the server digitally signs, saves, prints, and performs other operations on the final document. For example, the server saves the final employment contract in PDF format and emails it to the new employee.

[1441] In this way, the system supports users in creating legal documents quickly and efficiently, and enables the generation of high-quality legal documents that also take the user's feelings into consideration.

[1442] Example 2

[1443] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1444] Conventional legal support systems have difficulty not only accurately analyzing the consultation content provided by users and generating appropriate legal advice, but also responding while taking the user's emotions into consideration. Furthermore, the accuracy and efficiency of the generated legal documents are insufficient, and users have to spend a lot of time reviewing and revising the documents. Furthermore, few systems support both voice input and keyboard input, which reduces user convenience. There is a need to provide an integrated system that can solve these issues and provide users with high-quality, prompt legal support.

[1445] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes: means for accepting legal consultation input from a user; means for converting the input into text using speech recognition technology; means for analyzing the converted text data using a natural language processing engine to generate legal advice; means for determining the user's emotional state based on the analyzed text data and an emotion recognition engine; means for providing the generated legal advice to the user; means for selecting a legal document template in response to the user's document generation request; means for automatically inputting information based on the user's conversation content into the selected template; means for displaying the generated document to the user and regenerating it based on correction instructions; and means for saving and outputting the final document. This makes it possible to respond to various input methods from users and quickly provide high-quality legal support that takes their emotional state into consideration.

[1446] The "means for accepting input of legal consultation from the user" is a means for receiving the content of the consultation when the user makes a legal consultation to the system.

[1447] "Means for converting to text using speech recognition technology" refers to means that use technology to convert voice data uttered by a user into text data.

[1448] The "means for generating legal advice by analyzing using a natural language processing engine" is a means for generating legal advice based on the content of the user's consultation using a natural language processing engine that analyzes text data.

[1449] "Means for determining the emotional state of a user based on an emotion recognition engine" refers to means for determining the emotional state of a user (e.g., tension, anxiety, relief) using an emotion recognition engine based on the user's voice or text data.

[1450] The "means for providing generated legal advice to a user" refers to a means for conveying generated legal advice to a user.

[1451] The "means for selecting a legal document template" is a means for selecting, from a database, a legal document template that is suitable for a user's document generation request.

[1452] The "means for automatically inputting information based on the content of the user's conversation" is a means for automatically inputting information based on the content of the user's consultation or request into a selected template.

[1453] The "means for displaying the generated document to the user and regenerating it based on a correction instruction" refers to a means for displaying the generated document to the user and regenerating the document based on a correction instruction from the user.

[1454] The "means for saving and outputting the final document" refers to the means for digitally signing, saving, printing, emailing, etc. the final document.

[1455] This invention relates to an integrated legal support system that not only receives legal consultation input from users, provides legal advice based on that input, and generates legal documents, but also recognizes the user's emotions and responds appropriately. Specifically, this system is realized by combining voice recognition technology, a natural language processing engine, an emotion recognition engine, and an automatic document generation function.

[1456] The hardware required to implement this system includes the user's device (e.g., smartphone, tablet, computer) and server. The software uses speech recognition technology (e.g., Google Cloud Speech-to-Text), natural language processing engines (e.g., spaCy, BERT), emotion recognition engines (e.g., IBM Watson Tone Analyzer), and automatic document generation functions.

[1457] System Operation Overview

[1458] 1. A user accesses the system

[1459] A user accesses the system's application using a smartphone, tablet, or computer and enters their credentials on the login screen. The server validates the information and redirects the user to the main menu screen.

[1460] 2. Legal consultation via voice or text input

[1461] Users can use a microphone to provide legal advice by voice, or use a keyboard to input their consultation details in text. For example, if a user says, "I would like to create an employment contract," that information is entered into the system.

[1462] 3. Speech Recognition and Text Conversion

[1463] The device captures the user's voice and converts it to text using Google Cloud Speech-to-Text, which is then sent to a server.

[1464] 4. Text Analysis Using Natural Language Processing

[1465] The server analyzes the received text data using a natural language processing engine (e.g., spaCy, BERT) and generates legal advice by extracting relevant information based on the user's input (e.g., "Create an employment contract").

[1466] 5. Analysis of user emotions using an emotion recognition engine

[1467] The server inputs voice and text data into IBM Watson Tone Analyzer, which analyzes the user's emotional state (e.g., "tension" or "anxiety").

[1468] 6. Providing legal advice

[1469] The server generates legal advice based on the analysis results and sends it to the device, which then displays it to the user. For example, the advice might be, "Employment contracts must include job descriptions, salary, and working hours."

[1470] 7. Document template selection and auto-fill

[1471] When a user requests the generation of a legal document, the server selects an appropriate template and automatically inputs the user's conversation content (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") into that template.

[1472] 8. Viewing and Modifying Documents

[1473] The generated document is displayed on the terminal, and the user can check the contents. If necessary, they can provide instructions for correction, and the server will regenerate the document based on those instructions.

[1474] 9. Save and print the final document

[1475] The user performs a final check and then saves the completed document, digitally signs it, prints it, sends it by email, etc. The server executes these operations and saves the final version of the document.

[1476] Specific examples

[1477] For example, by entering the following prompt, the system can efficiently generate legal documents based on the user's needs:

[1478] "I would like to create an employment contract. I would like to be employed as an engineer with a monthly salary of 300,000 yen."

[1479] This prompt allows users to easily create the necessary legal documents and receive appropriate legal advice.

[1480] As described above, this system integrates voice recognition technology, a natural language processing engine, an emotion recognition engine, and automatic document generation functions, enabling it to provide users with high-quality, efficient legal support.

[1481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1482] Step 1: User accesses the system

[1483] Input: A user accesses the system's application using a smartphone, tablet, or computer and enters their username and password on the login screen.

[1484] Specific operation: The authentication information entered by the user is sent to the server via the terminal.

[1485] Data processing: The server checks the authentication information against a database to verify whether the user has a valid account.

[1486] Output: If the validation is successful, the server redirects the user to the main menu screen.

[1487] Step 2: Legal consultation via voice or text

[1488] Input: The user selects the "Legal Consultation" option on the main menu screen and then either uses the microphone to speak or uses the keyboard to enter text.

[1489] Specific behavior: The user speaks "I would like to create an employment contract" or types "I would like to create an employment contract" in text.

[1490] Output: The audio or text data is saved to the device.

[1491] Step 3: Speech recognition and text conversion

[1492] Input: Audio data stored on the device.

[1493] Specific operation: The device uses voice recognition technology (e.g., Google Cloud Speech-to-Text) to convert voice data into text data.

[1494] Data Processing: The process of analyzing the audio data and converting it into corresponding text takes place.

[1495] Output: The converted text data (e.g., "I would like to create an employment contract") is sent to the server.

[1496] Step 4: Text analysis using natural language processing

[1497] Input: The text data sent to the server.

[1498] Specific operation: The server analyzes the received text data using a natural language processing (NLP) engine (e.g., spaCy, BERT).

[1499] Data processing: Extract the user's inquiry content (e.g., "drafting an employment contract") from the text data and search for related legal information.

[1500] Output: Legal advice data based on the analysis results.

[1501] Step 5: Analyze user emotions using an emotion recognition engine

[1502] Input: Audio and text data.

[1503] Specific operation: The server inputs the voice data and text data into an emotion recognition engine (e.g., IBM Watson Tone Analyzer).

[1504] Data processing: Analyze the user's emotional state (e.g., "tension" or "anxiety") from the input data and assign an emotional tag.

[1505] Output: User's emotional state data.

[1506] Step 6: Providing legal advice

[1507] Input: Analysis results of the natural language processing engine and the emotion recognition engine.

[1508] Specific behavior: The server generates appropriate legal advice based on these results.

[1509] Data processing: The generated legal advice is customized to take into account the user's emotional state.

[1510] Output: Customized legal advice is sent to the terminal, which displays it to the user, for example, "Employment contracts must include job descriptions, salary, and working hours."

[1511] Step 7: Select a document template and auto-fill

[1512] Input: The user's document generation request.

[1513] Specific operation: The server selects a template suitable for the user's request from a database of legal document templates.

[1514] Data processing: The content of the user's conversation (e.g., "I will hire you as an engineer at a monthly salary of 300,000 yen") is automatically entered into the selected template.

[1515] Output: Completed auto-filled legal document template data.

[1516] Step 8: View and modify the document

[1517] Input: Auto-filled legal document template data.

[1518] Specific operation: The generated document is displayed on the terminal and the user checks the contents.

[1519] Data processing: The user inputs correction instructions as needed, which are then sent to the server.

[1520] Output: Document data that reflects the user's correction instructions.

[1521] Step 9: Save and print the final document

[1522] Input: The corrected document data.

[1523] Specific actions: The user performs a final review and specifies actions such as saving the completed document, digitally signing it, printing it, or sending it by email.

[1524] Data processing: The server generates a document in the specified format (e.g., PDF) and sends the data to the specified storage or destination.

[1525] Output: The final legal document data is saved and sent as needed.

[1526] (Application example 2)

[1527] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1528] Conventional legal consultation systems can accept legal consultations from users, perform speech recognition and text analysis, and provide legal advice, but they have the problem of being unable to respond to the user's emotions. Even when a user is feeling anxious or nervous, conventional systems are unable to recognize and respond to those emotions, creating a need for improved user experience. Furthermore, when it comes to generating legal documents, simply selecting a template and automatically entering information is not enough; a more user-friendly system that adapts to the user's emotional state is also needed.

[1529] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1530] In this invention, the server includes means for accepting legal consultation input from a user, means for converting the input into text using speech recognition technology, means for analyzing the converted text data and generating legal advice, means for analyzing the user's emotions, means for adjusting a response based on the analyzed emotions, means for selecting a legal document template in response to the user's document generation request, means for automatically inputting information based on the user's conversation content into the selected template, means for displaying the generated document to the user and regenerating it based on correction instructions, and means for saving and outputting the final document, thereby enabling optimal legal advice and document generation according to the user's emotional state.

[1531] "Legal consultation input" refers to the act of a user speaking to or inputting information about a legal problem or question into the system, and the content of that information.

[1532] "Speech recognition technology" is a technology that converts voice data into text data.

[1533] "Text data" refers to text information converted using voice recognition technology.

[1534] "Legal Advice" means professional opinions and suggestions provided based on a User's legal consultation input.

[1535] "Emotion analysis" is a technology that reads emotions from a user's voice data or text data and classifies those emotions.

[1536] "Adjusting response" refers to changing the legal advice provided or the way in which a conversation is conducted based on the analyzed user's emotions.

[1537] A "document generation request" refers to a user requesting the system to generate a specific legal document.

[1538] "Legal Document Template" refers to a template for creating a specific legal document.

[1539] "Auto-filling information" refers to automatically filling in required information into a selected template based on the user's input.

[1540] "Modification instructions" refer to instructions that a user requests to change a generated document.

[1541] "Final Document" refers to the completed legal document after user review and correction.

[1542] "Storing and outputting" refers to storing the final document in digital form and providing it to the user, such as by physically printing it, if necessary.

[1543] System configuration

[1544] The system according to the present invention comprises the following hardware and software. The hardware includes a device (such as a smartphone or a head-mounted display (HMD)) and a microphone for the user to receive legal consultation. The software includes speech recognition technology, an emotion analysis engine, a natural language processing engine, and an automatic document generation function.

[1545] Program Overview

[1546] 1. Speech Recognition Technology

[1547] The device receives voice input from the user and converts the voice data into text data using voice recognition technology (e.g., Python's speech_recognition library).

[1548] 2. Natural Language Processing

[1549] The server analyzes the converted text data using a natural language processing engine (e.g., NLPProcessor) and generates legal advice based on the legal consultation content.

[1550] 3. Emotion analysis

[1551] The server analyzes the user's emotions from the voice and text data using an emotion analysis engine (e.g., EmotionRecognizer). Based on the analyzed emotion data, the system adjusts the content of the legal advice and documents it generates.

[1552] 4. Generating Legal Documents

[1553] In response to a user's document generation request, the server selects a legal document template (e.g., LegalDocumentGenerator) and automatically fills in information based on the user's conversation.

[1554] 5. Viewing and Modifying Documents

[1555] The generated document is displayed to the user, and if the user requests corrections, it is regenerated. By repeating this process, the final document is completed.

[1556] 6. Saving and printing the final document

[1557] After the final confirmation, the document is digitally signed, saved, printed, etc. based on the user's instructions. The completed document is saved in PDF format and provided to the user.

[1558] Specific examples

[1559] When a user uses their smartphone to voice-input "I want to create a divorce agreement," the system converts the speech into text. The natural language processing engine then analyzes the text and generates the legal advice the user is seeking. At the same time, the sentiment analysis engine analyzes the user's emotions and, if it determines that the user is feeling anxious, makes suggestions to alleviate the user's anxiety.

[1560] An example of a prompt for a generative AI model is:

[1561] User Input:

[1562] I want to create a divorce agreement

[1563] Please tell me the details of the division of assets

[1564] Generated AI prompt:

[1565] "User wants to create divorce agreement. Feeling uneasy. Please provide appropriate legal advice and how to generate the document. Please include example sentences."

[1566] As in this example, the system can accept legal consultations from users, provide appropriate legal advice in real time, respond to their emotions, and generate, save, and output the final legal documents.

[1567] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1568] Step 1:

[1569] The user inputs the consultation details into the terminal by voice or text.

[1570] Input: The user speaks using a microphone or enters text using a keyboard.

[1571] Processing: The device uses voice recognition technology to convert the voice data into text data. If the input is text, it is treated as text data.

[1572] Output: Sent to the server as text data.

[1573] Step 2:

[1574] The server receives the text data and analyzes it using a natural language processing engine.

[1575] Input: Text data sent from the terminal.

[1576] Processing: The server's natural language processing engine analyzes the text data and extracts the user's legal consultation details.

[1577] Output: Extracted legal consultation content.

[1578] Step 3:

[1579] The server analyzes the user's emotions and obtains the results.

[1580] Input: User voice and text data.

[1581] Processing: The server's emotion analysis engine analyzes the audio and text data to recognize emotional states (e.g., anxiety, tension).

[1582] Output: Emotion analysis results.

[1583] Step 4:

[1584] The server generates appropriate legal advice based on the content of the legal consultation and the results of sentiment analysis.

[1585] Input: Legal consultation content and sentiment analysis results.

[1586] Processing: A natural language processing engine integrates legal consultation content with sentiment analysis results to generate tailored legal advice for the user.

[1587] Output: The generated legal advice.

[1588] Step 5:

[1589] The server transmits legal advice to the terminal and provides it to the user.

[1590] Input: The generated legal advice.

[1591] Processing: The server sends the legal advice to the device, which displays it to the user.

[1592] Output: The legal advice that is displayed to the user.

[1593] Step 6:

[1594] The user makes a document generation request.

[1595] Input: The user's document generation request.

[1596] Process: The user sends a document generation request to the server through the terminal.

[1597] Output: A request to the server to generate the document.

[1598] Step 7:

[1599] The server selects the appropriate legal document template and auto-fills the information.

[1600] Input: Document generation request and user consultation.

[1601] Processing: The server selects an appropriate template from a legal document template database and automatically fills in information based on the user's conversation.

[1602] Output: The generated legal document.

[1603] Step 8:

[1604] The server sends the generated document to the terminal and displays it to the user.

[1605] Input: The generated legal document.

[1606] Process: The server sends the document to the terminal, which displays it to the user.

[1607] Output: The document that is displayed to the user.

[1608] Step 9:

[1609] The user checks the document and gives instructions for corrections as necessary.

[1610] Input: The user checks the displayed document and gives instructions for correction if necessary.

[1611] Processing: The server regenerates the document based on the user's correction instructions.

[1612] Output: The corrected document.

[1613] Step 10:

[1614] The server stores and outputs the final document.

[1615] Input: Final revised document.

[1616] Processing: The server stores the final document digitally and prints or emails it as needed.

[1617] Output: storing in digital form or providing to users.

[1618] The above steps enable optimal legal advice and document generation according to the user's emotional state.

[1619] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1620] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1621] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1622] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1623] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1624] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1625] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1626] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1627] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1628] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1629] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1630] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1631] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1632] 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.

[1633] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1634] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1635] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1636] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1637] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1638] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1639] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1640] The following is further disclosed regarding the above embodiment.

[1641] (Claim 1)

[1642] means for accepting legal consultation input from a user;

[1643] A means of converting that input into text using voice recognition technology;

[1644] means for analyzing the converted text data to generate legal advice;

[1645] a means for providing the generated legal advice to a user;

[1646] means for selecting a legal document template in response to a user's document generation request;

[1647] A means for automatically inputting information based on the content of the user's conversation into the selected template;

[1648] means for displaying the generated document to a user and regenerating the document based on correction instructions;

[1649] means for saving and outputting the final document;

[1650] A system including:

[1651] (Claim 2)

[1652] 10. The system of claim 1, wherein the system accepts both voice and keyboard input.

[1653] (Claim 3)

[1654] 10. The system of claim 1, wherein an appropriate legal document template is automatically selected based on the content of the user's legal consultation.

[1655] "Example 1"

[1656] (Claim 1)

[1657] means for accepting legal consultation input from a user;

[1658] A means of converting that input into text using voice recognition technology;

[1659] means for analyzing the converted text data to generate legal advice;

[1660] a means for providing the generated legal advice to a user;

[1661] means for selecting a legal document template in response to a user's document generation request;

[1662] A means for automatically inputting information based on the content of the user's conversation into the selected template;

[1663] means for displaying the generated document to a user and regenerating the document based on correction instructions;

[1664] means for saving and outputting the final document;

[1665] means for using a natural language processing engine to convert the audio data;

[1666] a means for using the legal knowledge base for document generation;

[1667] means for outputting a document with a digital signature;

[1668] A system including:

[1669] (Claim 2)

[1670] 10. The system of claim 1, wherein the system accepts both voice and keyboard input.

[1671] (Claim 3)

[1672] 10. The system of claim 1, wherein an appropriate legal document template is automatically selected based on the content of the user's legal consultation.

[1673] "Application Example 1"

[1674] (Claim 1)

[1675] means for accepting legal consultation input from a user;

[1676] A means of converting that input into text using voice recognition technology;

[1677] means for analyzing the converted text data to generate legal advice;

[1678] a means for providing the generated legal advice to a user;

[1679] means for selecting a legal document template in response to a user's document generation request;

[1680] A means for automatically inputting information based on the content of the user's conversation into the selected template;

[1681] means for displaying the generated document to a user and regenerating the document based on correction instructions;

[1682] means for saving and outputting the final document;

[1683] A means of providing legal advice within the virtual storefront;

[1684] means for accepting input via smart glasses or a smartphone;

[1685] A system including:

[1686] (Claim 2)

[1687] 10. The system of claim 1, wherein the system accepts both voice and keyboard input.

[1688] (Claim 3)

[1689] 10. The system of claim 1, wherein an appropriate legal document template is automatically selected based on the content of the user's legal consultation.

[1690] "Example 2: Combining Emotion Engines"

[1691] (Claim 1)

[1692] means for accepting legal consultation input from a user;

[1693] A means of converting that input into text using voice recognition technology;

[1694] A means for analyzing the converted text data with a natural language processing engine to generate legal advice;

[1695] means for determining the emotional state of the user based on the analyzed text data and an emotion recognition engine;

[1696] a means for providing the generated legal advice to a user;

[1697] means for selecting a legal document template in response to a user's document generation request;

[1698] A means for automatically inputting information based on the content of the user's conversation into the selected template;

[1699] means for displaying the generated document to a user and regenerating the document based on correction instructions;

[1700] means for saving and outputting the final document;

[1701] A system including:

[1702] (Claim 2)

[1703] 10. The system of claim 1, wherein the system accepts both voice and keyboard input.

[1704] (Claim 3)

[1705] 2. The system according to claim 1, wherein the system automatically selects an appropriate legal document template based on the content of the legal consultation of the user and responds according to the user's emotional state.

[1706] "Application example 2 when combining emotion engines"

[1707] (Claim 1)

[1708] means for accepting legal consultation input from a user;

[1709] A means of converting that input into text using voice recognition technology;

[1710] means for analyzing the converted text data to generate legal advice;

[1711] a means for providing the generated legal advice to a user;

[1712] means for analyzing user emotions;

[1713] a means for adjusting a response based on the analyzed emotion;

[1714] means for selecting a legal document template in response to a user's document generation request;

[1715] A means for automatically inputting information based on the content of the user's conversation into the selected template;

[1716] means for displaying the generated document to a user and regenerating the document based on correction instructions;

[1717] means for saving and outputting the final document;

[1718] A system including:

[1719] (Claim 2)

[1720] 10. The system of claim 1, wherein the system accepts both voice and keyboard input.

[1721] (Claim 3)

[1722] 10. The system of claim 1, wherein the system automatically selects an appropriate legal document template based on the content of the legal consultation and sentiment analysis of the user. [Explanation of symbols]

[1723] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for accepting legal consultation input from a user; A means of converting that input into text using voice recognition technology; means for analyzing the converted text data to generate legal advice; a means for providing the generated legal advice to a user; means for selecting a legal document template in response to a user's document generation request; A means for automatically inputting information based on the content of the user's conversation into the selected template; means for displaying the generated document to a user and regenerating the document based on correction instructions; means for saving and outputting the final document; A system including:

2. 10. The system of claim 1, wherein the system accepts both voice and keyboard input.

3. 10. The system of claim 1, wherein an appropriate legal document template is automatically selected based on the content of the user's legal consultation.

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