System

Abstract

A system is provided.SOLUTION: Means for a user to input a legal question; means for a server to receive the user's question, parse the question using a natural language processing algorithm, and extract keywords and intent; and means for the server to send a query to a legal knowledge base based on the extracted keywords; A system comprising: means for obtaining relevant legal information; means for a server to generate an answer based on the obtained information using a AI model; means for the server to send the generated answer to a user's device, wherein the device displays the answer to the user; and means for providing access to a paid legal expert consultation when the user faces a serious legal issue.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] In modern society, the use of digital content has become commonplace, making it easy for legal issues to arise, such as copyright infringement, illegal downloading, and unauthorized video distribution. Furthermore, many individuals lack legal knowledge, putting them at risk of unwittingly engaging in illegal activities. Given the lack of convenient means to provide prompt and appropriate legal advice, users need the ability to minimize legal risks and safely use digital content. Furthermore, when faced with serious legal issues, they need a way to smoothly access expert assistance. [Means for solving the problem]

[0005] This invention provides a means for users to input legal questions, and a server receives and analyzes the questions. Specifically, the server analyzes the questions using a natural language processing algorithm to extract keywords and intent. The server then sends a query to a legal knowledge base based on the extracted keywords to obtain relevant legal information. Based on the obtained information, the server uses an AI model to generate an answer, which is then sent and displayed on the user's device. Furthermore, when users face serious legal issues, the server provides access to paid consultations with legal experts, ensuring prompt and appropriate legal assistance. The server also collects and analyzes user feedback and updates the AI ​​model to improve the accuracy of future answers. This minimizes legal risks and provides an environment where digital content can be used safely.

[0006] "User" means any person or entity that uses the System to enter legal questions and receive answers.

[0007] "Device" refers to an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter questions and receive answers.

[0008] "Server" refers to a central processing unit responsible for receiving and analyzing user questions, generating and transmitting answers.

[0009] A "natural language processing algorithm" is a program system that analyzes text entered by a user and extracts the subject and keywords from that text.

[0010] "Keywords" are key words or phrases extracted from a user's question that form the basis of a query to the legal knowledge base.

[0011] "Intent" refers to the specific information or answer the user is seeking through the question.

[0012] "Legal knowledge base" means a database that collects legal information, related precedents, legal documents, etc.

[0013] "Query" refers to an inquiry sent to a database to retrieve information.

[0014] "AI model" refers to a computational model that uses artificial intelligence technology to generate answers for users based on acquired information.

[0015] "Feedback" refers to information such as a user's satisfaction with the answers provided, their opinions, and comments.

[0016] "Consultation" means professional advice services, including paid assistance provided to Users when they face serious legal issues. [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 present invention is a system for enabling users to obtain quick and accurate answers to legal questions. The operation of this system will now be described in detail.

[0039] First, the user enters their legal question in text format into the terminal. The terminal provides a user interface with a text box for entering the question and a submit button. The user uses this input form to enter their question and then presses the submit button.

[0040] Next, the device sends the user's question to the server in the form of an HTTP request, which the server receives and retrieves the question text.

[0041] The server uses natural language processing algorithms to analyze the text based on the received question. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[0042] Based on these keywords, the server queries a legal knowledge base to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns the appropriate information for the query.

[0043] Based on the acquired information, the server uses an AI model to generate a response. This response contains specific content that is easy for the user to understand. For example, it can be output as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0044] The generated answer is sent from the server to the device, which displays the answer on the user's screen, possibly with links to additional information or relevant legal resources, if necessary.

[0045] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, allowing the user to receive professional assistance.

[0046] Finally, the server collects user feedback and uses it to update the AI ​​model to improve the accuracy of future answers, a process that continuously improves the entire system.

[0047] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content, and is extremely beneficial to users as it allows them to quickly receive expert assistance for even serious legal issues.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] An interface is displayed for the user to enter legal questions into the terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[0051] Step 2:

[0052] The device sends the user's question in text format to the server, which sends the question to the server as an HTTP request.

[0053] Step 3:

[0054] The server receives the HTTP request, retrieves the question text, and prepares it for analysis.

[0055] Step 4:

[0056] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[0057] Step 5:

[0058] The server sends a query to a legal knowledge base (database) based on the extracted keywords, where the query is an inquiry to search for relevant legal information.

[0059] Step 6:

[0060] The server retrieves relevant information from a legal knowledge base, which returns relevant legal information, precedents, and legal documents.

[0061] Step 7:

[0062] The server uses an AI model based on the information it acquires to generate specific answers for the user, which are designed to be easy for the user to understand.

[0063] Step 8:

[0064] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[0065] Step 9:

[0066] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[0067] Step 10:

[0068] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[0069] Step 11:

[0070] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[0071] Step 12:

[0072] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[0073] Example 1

[0074] 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."

[0075] There are challenges for users, such as the difficulty of getting fast and accurate answers to legal questions over the Internet, and the difficulty of quickly receiving paid legal assistance when users face serious legal issues. Furthermore, there is a need for the system to effectively utilize user feedback and be continuously improved.

[0076] 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.

[0077] In this invention, the server includes a means for receiving a user's question and analyzing it using a natural language processing algorithm, a means for sending a query to a legal knowledge base based on the extracted keywords to obtain information, and a means for generating an answer using a generative AI model based on the obtained information. This allows users to obtain quick and accurate legal answers, and enables them to quickly receive support from paid legal experts when facing serious legal issues. In addition, by collecting user feedback and updating the generative AI model, the accuracy of the next answer can be improved.

[0078] "User" means any person or entity that utilizes the System to enter legal questions and receive answers.

[0079] A "terminal" is an electronic device through which a user enters legal questions and displays responses from a server.

[0080] A "server" is a central computing device that receives a user's question, analyzes it, generates an answer, and sends it to the terminal.

[0081] A "natural language processing algorithm" is a technology that analyzes text entered by a user and extracts meaning and keywords.

[0082] "Keywords" are important words and phrases extracted from the question entered by the user to identify the meaning of the text.

[0083] A "legal knowledge base" is a database that stores legal information, including copyright law, legal precedents, and regulatory information.

[0084] A "generative AI model" is an artificial intelligence model that generates appropriate answers for users based on information obtained from a legal knowledge base.

[0085] An "answer" is a response message generated by the server in response to a user's question.

[0086] "Feedback" is the user's evaluation or opinion of the system's response.

[0087] A "paid legal consultation" is a paid legal advice service provided by a professional lawyer.

[0088] The present invention is a system for allowing a user to input a legal question and receive a prompt and appropriate answer based on the question, the system including a terminal, a server, and a legal knowledge base.

[0089] First, the user enters a legal question in text format into the device. The device provides a user interface, displaying a text box for entering the question and a submit button. For example, the user enters the question, "Is it legal to use music downloaded from YouTube for personal use?" and presses the submit button. At this time, the device detects the click event of the submit button, obtains the entered question text, and proceeds to the next step.

[0090] The device sends the user's question to the server in the form of an HTTP request. The HTTP request includes the question text. The device then generates an HTTP POST request including the question text and sends the data to the specified endpoint. This establishes network communication and the data reaches the server.

[0091] The server receives the HTTP request and retrieves the question text. It then uses natural language processing algorithms to analyze the text and extract the subject and keywords of the question. For example, if the server receives the question "Is it legal to download music from YouTube for personal use?", it uses a natural language processing library to extract the keywords "YouTube," "download," "personal use," and "legal."

[0092] The server sends a query to a legal knowledge base based on the extracted keywords to retrieve relevant legal information, for example, the server retrieves information about "copyright law" and "personal use" from the legal knowledge base.

[0093] Next, the server uses the generative AI model to generate a response based on the acquired legal information. For example, if the legal information returned is "personal use may be a copyright infringement," the generative AI model uses that information to generate a response such as "downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0094] The generated answer is sent from the server to the device. The device displays the answer received from the server on the user's screen. If necessary, links to additional information or relevant legal resources are also displayed. For example, the device analyzes the received answer text and updates the user interface to display the text. A message is displayed on the screen stating, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0095] Furthermore, if the user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. The user can click on this link to receive professional assistance. For example, the device may display a link on the screen that reads, "If you need more information, you can consult with a legal professional by clicking this link." and the user can click on it.

[0096] Finally, the server collects user feedback and uses it to update the generative AI model to improve the accuracy of future answers. For example, if a user rates the answer as "helpful," the server stores that feedback in a database and periodically uses it as training data for the generative AI model. This allows the entire system to continuously improve, improving the accuracy of future answers.

[0097] Prompt Sentence Examples

[0098] Here is an example prompt:

[0099] "Is it legal to download music from YouTube for personal use?"

[0100] "Is it illegal to post screenshots from a movie on a website?"

[0101] "Can I use free materials I find online for commercial purposes?"

[0102] In this way, users can minimize legal risks and safely use digital content. Furthermore, the entire system is continuously improved by updating the generative AI model based on feedback.

[0103] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0104] Step 1:

[0105] Users enter and submit legal questions.

[0106] What it does: The device provides a text box and a submit button for the user to enter a question. The user enters a question such as "Is it legal to download music from YouTube for personal use?" and presses the submit button.

[0107] Input: Legal question text entered by the user

[0108] Output: Question text collected by the device

[0109] Step 2:

[0110] The device sends the user's question to the server.

[0111] Specific operation: The device generates an HTTP POST request containing the question text and sends it to the server. Network communication is established and the data arrives at the server.

[0112] Input: Question text collected by the device

[0113] Output: An HTTP request containing the question text arrives at the server.

[0114] Step 3:

[0115] The server receives and parses the question text.

[0116] What it does: The server receives an HTTP request, retrieves the question text, and uses a natural language processing algorithm to extract keywords such as "YouTube," "download," "personal," and "legal."

[0117] Input: HTTP request containing the question text

[0118] Output: Extracted keywords

[0119] Step 4:

[0120] The server queries the legal knowledge base to retrieve the information.

[0121] What happens: The server generates a database query using the keywords "copyright law" and "personal use" and performs a search against the legal knowledge base. Relevant legal information is retrieved from the database.

[0122] Input: Extracted keywords

[0123] Output: Information retrieved from the legal knowledge base

[0124] Step 5:

[0125] The server generates an answer using a generative AI model based on the information it obtains.

[0126] Specific operation: The server uses a generative AI model to generate an answer based on the legal information it has obtained. For example, it might generate an answer such as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0127] Input: Information retrieved from the legal knowledge base

[0128] Output: Answer text provided to the user

[0129] Step 6:

[0130] The server sends the generated response to the terminal.

[0131] Specific operation: The server generates an HTTP response containing the answer text and sends it to the device. The data reaches the device via the network.

[0132] Input: Answer text provided to the user

[0133] Output: HTTP response containing the answer text

[0134] Step 7:

[0135] The device displays the answer to the user.

[0136] What happens: The device parses the received response text and updates the user interface, displaying the response text on the screen and, if necessary, providing links to relevant legal resources.

[0137] Input: HTTP response containing the answer text

[0138] Output: The answer text and link that is displayed to the user

[0139] Step 8:

[0140] The device will display a link to access a paid legal consultation (if required).

[0141] What it does: The device displays a link on the screen that says, "For more information, you can contact a legal professional by following this link." The user can click it.

[0142] Input: Expert Consultation Link Needed

[0143] Output: A user-clickable consultation link

[0144] Step 9:

[0145] The server collects feedback and updates the generative AI model.

[0146] What it does: The server collects user feedback, stores it in a database, and periodically uses it as training data for the generative AI model, improving the accuracy of future answers.

[0147] Input: User feedback

[0148] Output: Updated generative AI model and improved answer accuracy

[0149] (Application example 1)

[0150] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0151] When users of autonomous vehicles encounter legal questions or problems, there is a lack of means to respond quickly and appropriately. In particular, there is a need for a system that can provide real-time answers to legal questions that arise while driving. To solve this problem, a system is needed that allows users to input questions through an intuitive user interface, including voice input, and quickly provides appropriate legal advice.

[0152] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0153] In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question and analyze the question using a natural language processing algorithm to extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for providing access to paid consultations with legal experts when the user faces a serious legal issue; means for inputting and transmitting the legal question via a user interface in the autonomous vehicle; means for inputting the legal question in voice form using the vehicle's voice input system; and means for providing an answer via the vehicle's touchscreen or voice output system, thereby enabling the user to receive prompt and appropriate legal advice while driving.

[0154] "User interface" means the means of input and output that a user uses to interact with a system, including touchscreens and voice input systems in autonomous vehicles.

[0155] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language, using a series of algorithms including text analysis and keyword extraction.

[0156] A "legal knowledge base" is a database that stores structured legal information, such as copyright law, case law, and regulatory information, and is intended to provide appropriate legal information in response to queries.

[0157] An "AI model" is a mathematical model that uses artificial intelligence technology to generate appropriate outputs for specific inputs, and is responsible for generating answers to legal questions.

[0158] A "voice input system" is a device or technology that allows a user to input instructions into a system through speech, and converts speech into text using speech recognition technology.

[0159] A "touch screen" is an input device that allows users to operate the device by touching the screen, allowing them to intuitively input questions and check answers.

[0160] A "legal advice system" is a set of computer systems that uses technologies such as natural language processing and AI models to provide appropriate advice on legal questions.

[0161] "Feedback" is information provided by users regarding their satisfaction with the system's responses and suggestions for improvement, and is used as data for improving the system.

[0162] "Consultation" means consultation to obtain expert advice on a specific issue, including conversations with paid legal professionals.

[0163] An "autonomous vehicle" is a vehicle that drives automatically using artificial intelligence and various sensors, and is equipped with technology that minimizes human intervention.

[0164] The system of the present invention is a legal advice system installed in an autonomous vehicle, and aims to provide users with prompt and appropriate answers to legal questions that arise while driving. This system operates by combining a user interface, natural language processing, a legal knowledge base, an AI model, and a voice input / output device.

[0165] System configuration

[0166] 1. User Interface:

[0167] It provides a means for users to input legal questions using touchscreens and voice input systems within autonomous vehicles.

[0168] 2. Voice input system:

[0169] It uses the SpeechRecognition library to recognize the user's speech and converts it to text using the Google Speech Recognition API. For example, if a user asks, "I didn't see that road sign just now. Does that mean I'm speeding?", the system will convert that speech to text.

[0170] 3. Data transmission:

[0171] Questions entered in text format via a voice input system or touchscreen are sent from the car's computer to the server in the form of an HTTP request.

[0172] 4. Text Analysis (Natural Language Processing):

[0173] The server analyzes the received question text using a natural language processing algorithm. As a result of the analysis, it extracts key keywords and themes. For example, in response to the question, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[0174] 5. Obtaining information from the legal knowledge base:

[0175] The server then queries a legal knowledge base based on the extracted keywords to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns appropriate information for the query.

[0176] 6. Answer generation by AI model:

[0177] Based on the legal information obtained by the server, an AI model is used to generate a response in a user-friendly format. For example, the output would be something like, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0178] 7. Suggested answers:

[0179] The generated answers are then sent back into the vehicle and presented to the user via the touchscreen or via a voice output system, which uses the pyttsx3 library to play the text aloud.

[0180] 8. Additional options:

[0181] For serious legal issues, a link is also provided to allow for paid consultation with a legal expert using the vehicle's internet connection.

[0182] 9. Feedback collection and system learning:

[0183] The server collects user feedback and uses it as data to improve the accuracy of answers across the entire system, which will improve the accuracy of answers from the next time onwards.

[0184] Specific examples

[0185] As a concrete example, imagine a user asks the following question:

[0186] Question: "I didn't see the road sign just now. Does that count as speeding?"

[0187] Answer: "Even if you don't see the road signs, you still need to obey the speed limit. It may be a legal violation."

[0188] Prompt Sentence Examples

[0189] User question: "I didn't see the road sign just now, does that mean I'm speeding?"

[0190] Keywords: road signs, speeding

[0191] Search for relevant information in a legal knowledge base and generate the answer: "Even if you don't see the road sign, you must obey the speed limit. It may be a legal violation."

[0192] The system of this invention aims to provide quick and appropriate answers to legal questions while driving, allowing users to use self-driving vehicles with peace of mind.

[0193] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0194] Step 1:

[0195] The user enters a legal question.

[0196] Specifically, a user inputs a question using a touchscreen or voice input system in an autonomous vehicle. When using a voice input system, the user verbally states the question, which the SpeechRecognition library converts into text. The input is the user's question, and the output is a text question.

[0197] Step 2:

[0198] The autonomous vehicle's terminal sends the question to the server.

[0199] Specifically, a text question is sent to the server in the form of an HTTP request. The input is the text question, and the output is an HTTP request to the server.

[0200] Step 3:

[0201] The server receives the question and analyzes it using natural language processing algorithms.

[0202] Specifically, the received text is parsed using natural language processing (NLP) algorithms (e.g., spaCy or NLTK libraries) to extract key keywords and intent, where the input is a textual question and the output is the extracted keywords and themes.

[0203] Step 4:

[0204] The server sends a query to a legal knowledge base based on the extracted keywords.

[0205] Specifically, the extracted keywords are used to query a legal knowledge base (database) to retrieve relevant legal information, where the input is the extracted keywords and the output is the legal information as a query result.

[0206] Step 5:

[0207] The server generates answers using an AI model based on the information it obtains.

[0208] Specifically, an AI model (such as GPT-4) is used to generate an answer based on the acquired legal information in a format that is easy for the user to understand. The input is information obtained from the legal knowledge base, and the output is the generated answer.

[0209] Step 6:

[0210] The server generates a response and sends it to the user's device.

[0211] Specifically, the generated answer is sent to the autonomous vehicle's terminal as an HTTP response. The input at this time is the generated answer, and the output is the HTTP response to the terminal.

[0212] Step 7:

[0213] The device displays the answer to the user.

[0214] Specifically, the answer is displayed on a touchscreen, or the answer is played aloud using a voice output system, which uses the pyttsx3 library to convert text to speech, where the input is the answer provided by the server, and the output is the information the user receives visually or audibly.

[0215] Step 8:

[0216] Providing paid legal consultations when users face serious legal issues.

[0217] Specifically, when a user requests additional advice, for example, a link to access a paid consultation is displayed on the touch screen, where the input is the user's request and the output is the link to access the consultation.

[0218] Step 9:

[0219] The server collects user feedback and updates the AI ​​model.

[0220] Specifically, it collects user-provided feedback, analyzes that data, adds it to the AI ​​model's training dataset, and retrains the model to improve answer accuracy in future iterations. The input is the user feedback, and the output is an updated AI model.

[0221] 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.

[0222] The present invention is a system that allows users to get fast and accurate answers to their legal questions. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the tone and content of the answers based on that information.

[0223] First, the user enters their legal question in text format into the terminal. At this time, the terminal displays a user interface, providing a text box for entering the question and a submit button. The user uses this interface to enter the question and presses the "Submit" button.

[0224] Next, the device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with features such as facial recognition and voice analysis, and these emotion engines are used to analyze the user's emotions in real time.

[0225] After the server receives the question, it uses natural language processing algorithms to analyze the text. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server will extract the keywords "YouTube," "download," "personal use," and "legal."

[0226] Based on the extracted keywords, the server sends a query to a legal knowledge base (database) to retrieve relevant legal information. The legal knowledge base includes copyright law, legal precedents, regulatory information, etc., and returns appropriate information for the query.

[0227] Based on the information obtained, the server uses an AI model to generate a response. This response is adjusted taking into account the user's emotional state. For example, if the emotion engine detects that the user is anxious, the server will create a response in a gentler, more reassuring tone. For example, it might say, "Downloading music from YouTube for personal use may be a copyright infringement. If you are concerned, we recommend obtaining permission from the copyright holder."

[0228] The generated answer is sent from the server to the device, which displays the answer on the user's screen, along with links to additional information and relevant legal resources, if necessary.

[0229] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, which will take the user through the process of obtaining professional assistance.

[0230] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[0231] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content. It also takes into account the user's emotional state to provide more personalized and friendly answers. This is extremely beneficial for users, as they can quickly receive expert assistance even for serious legal issues.

[0232] The processing flow will be explained below.

[0233] Step 1:

[0234] The user operates an interface for entering legal questions into a terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[0235] Step 2:

[0236] The device asks the user questions and uses facial recognition and voice analysis to collect emotional data, analyzing the user's emotional state (e.g., anxiety, anger, excitement, etc.) from their facial expressions and voice tone.

[0237] Step 3:

[0238] The device sends the user's question text and emotion data to the server in the form of an HTTP request.

[0239] Step 4:

[0240] The server receives the HTTP request and retrieves the question text and emotion data.

[0241] Step 5:

[0242] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[0243] Step 6:

[0244] The server sends a query to a legal knowledge base (database) based on the extracted keywords to search for relevant legal information.

[0245] Step 7:

[0246] The server retrieves relevant information from a legal knowledge base, returning legal information, precedents, legal documents, etc.

[0247] Step 8:

[0248] The server uses an AI model to generate a response based on the information acquired and the user's emotional data. The tone and content of the response are adjusted according to the emotional data. For example, if the user is anxious, the response will be generated in a gentler tone.

[0249] Step 9:

[0250] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[0251] Step 10:

[0252] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[0253] Step 11:

[0254] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[0255] Step 12:

[0256] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[0257] Step 13:

[0258] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[0259] Example 2

[0260] 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."

[0261] Previously, when users had legal questions, it was difficult to get a quick and accurate answer, and it was not possible to respond appropriately based on the user's emotional state. Furthermore, when users faced serious legal issues, it was difficult to receive appropriate support because there was no way to quickly access paid legal experts.

[0262] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for a terminal to analyze the user's emotions; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using a generative AI model based on the information obtained; means for the server to adjust the answer generated by the server based on the user's emotional state; means for the server to send the answer generated by the server to the user's terminal and for the terminal to display the answer to the user; and means for providing access to paid consultations with legal experts when the user faces a serious legal problem. This allows users to receive prompt and accurate legal advice and personalized responses according to their emotional state. It also allows users to receive prompt expert support even for serious legal issues.

[0263] "User" means any person who uses the System to enter legal questions and receive answers.

[0264] "Terminal" means the electronic device used by a User to enter legal questions and view answers.

[0265] "Emotion analysis" refers to the technology and process by which a device detects and analyzes a user's emotional state.

[0266] "Server" refers to the central processing system for processing legal inquiries received from Users, generating answers, and returning them to Users.

[0267] A "natural language processing algorithm" refers to an algorithm that analyzes text questions and extracts keywords and intent.

[0268] "Keywords" refer to important words or phrases extracted from a user's question.

[0269] A "legal knowledge base" refers to a database that stores legal information (e.g., laws, precedents, regulatory information, etc.).

[0270] "Query" refers to a search instruction sent by a server to a legal knowledge base.

[0271] "Generative AI model" refers to an artificial intelligence model that generates answers based on acquired legal information.

[0272] "Answer" refers to the response provided by the server to the user's question using a generative AI model.

[0273] "Feedback" refers to ratings and comments on system responses collected from users.

[0274] "Paid legal consultation" means legal consultation services provided for a fee.

[0275] "Access Link" means a connection that directs a user to a paid consultation with a legal professional.

[0276] "Tuning" refers to the process of changing the tone and content of the generated answers depending on the user's emotional state.

[0277] This invention is a system that allows users to quickly and accurately obtain answers to legal questions. Furthermore, it provides personalized responses by incorporating an emotion engine that recognizes the user's emotions and adjusts the tone and content of the response based on that information. To effectively implement this system, the following hardware and software are required:

[0278] First, the user enters their legal question in text format into the device. At this time, a user interface is displayed on the device, providing a text box for entering the question and a submit button. The user uses this interface to enter their question and presses the "Submit" button. An example of a question that a user might enter is, "Is it okay to watch a movie I downloaded online with my friends?"

[0279] The device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with a facial recognition camera and a voice analysis microphone, and these are used to analyze the user's emotions in real time using an emotion engine. Emotion analysis determines, for example, whether the user is feeling anxious based on their facial expressions and tone of voice when entering a question.

[0280] After the server receives the question, it performs text analysis using natural language processing algorithms (e.g., SpaCy or NLTK). This analysis extracts topics and keywords from the question. For example, if a user asks, "Is it okay to watch a movie I downloaded online with my friends?", the server extracts the keywords "online," "download," "movie," "watch with friends," and "okay."

[0281] Next, the server sends a query to a legal knowledge base (e.g., a database built with SQL) based on the extracted keywords to retrieve relevant legal information. The legal knowledge base stores copyright law, precedents, regulatory information, and other information, and returns appropriate information in response to the query. Based on the information retrieved by the server, a generative AI model (e.g., GPT-3) is used to generate an answer to the user's question.

[0282] The generated answer is adjusted to take into account the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server will create a gentler, more reassuring tone of response, such as, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[0283] The server then sends the generated answer to the device, which then displays it on the user's screen. The answer may also include links to additional information and related legal resources. Additionally, if the user faces a serious legal problem, the device may display a link to access a paid legal consultation. Clicking on this link will take the user through the process of obtaining professional assistance.

[0284] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[0285] Examples of prompts:

[0286] "Is it legal to watch movies downloaded online with friends?"

[0287] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0288] Step 1:

[0289] The user enters a legal question in text format using the device's user interface and presses the "Submit" button. This obtains the legal question as input from the end user. An example of a specific prompt sentence is "Is it okay to watch a movie downloaded online with a friend?"

[0290] Step 2:

[0291] The device receives the text entered by the user and analyzes the user's emotions in real time using a facial recognition camera and a voice analysis microphone. The emotion analysis engine determines the user's emotional state from their facial expressions and tone of voice. The results of this analysis (e.g., the user is anxious) are used as input for the next step.

[0292] Step 3:

[0293] The device sends the user's question and the emotion analysis results to the server in the form of an HTTP request. The server receives this request and obtains the input text and emotion data. As a result, the server obtains the user's question and information about their emotional state as input.

[0294] Step 4:

[0295] The server analyzes the received question text using a natural language processing algorithm (e.g., SpaCy or NLTK). During this analysis, themes and keywords are extracted from the question. For example, keywords such as "online," "download," "movie," "watch with friends," and "okay" are extracted and used as input for the next step.

[0296] Step 5:

[0297] The server sends a query to a legal knowledge base (e.g., an SQL database) based on the extracted keywords, which searches for relevant legal information (e.g., copyright law, legal precedents, regulatory information, etc.) and obtains the information obtained from the query as output.

[0298] Step 6:

[0299] The server uses a generative AI model (e.g., GPT-3) to generate an answer based on the legal information it obtains. The answer is adjusted based on the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server might generate a gentle answer saying, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[0300] Step 7:

[0301] The server generates a response and sends it to the user's device. The device receives the response and displays it on the user's screen. This allows the user to obtain legal advice through their device. Links to relevant legal resources are also displayed, if necessary.

[0302] Step 8:

[0303] If a user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. For example, a link such as "Click here for more information" will be displayed, and the user can click it to begin the process of receiving professional assistance.

[0304] Step 9:

[0305] The server collects user feedback. User ratings and comments are collected and stored in a database. The server analyzes this feedback and updates the generative AI model to improve the accuracy of future answers. This process continuously improves the entire system.

[0306] (Application example 2)

[0307] 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."

[0308] For food delivery services, responding quickly and accurately to customer questions and complaints is crucial to maintaining customer satisfaction. However, previous systems struggled to generate personalized responses that took into account the user's emotional state. They also lacked the means to quickly provide appropriate legal information and expert assistance. This sometimes resulted in delayed responses to user complaints, leading to lower customer satisfaction.

[0309] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for the terminal to recognize the user's emotional state using facial recognition and voice analysis; means for the server to adjust the tone of the answer based on the recognized emotional state; and means for providing access to paid expert consultations when the user faces a serious legal problem. This enables personalized answers to be provided based on the user's emotional state and rapid provision of legal information and expert assistance.

[0310] A "means for users to enter legal questions" is a system that provides an interface, text box, and submit button for users to enter legal questions in text format using a terminal.

[0311] A "natural language processing algorithm" is a machine learning algorithm for understanding, analyzing, and processing human language, and is a technology used to extract keywords and intent from text data.

[0312] A "legal knowledge base" is a database that stores legal information and data, including copyright law, legal precedents, and regulatory information.

[0313] An "AI model" is an artificial intelligence model trained by machine learning algorithms and used to generate appropriate answers based on input data.

[0314] "Facial recognition" is a technology that uses image processing technology to detect a user's face and analyze their facial expressions and features.

[0315] "Voice analysis" is a technology that analyzes voice data and recognizes the user's tone of voice and emotions.

[0316] "Emotional state" refers to a psychological state inferred from a user's facial expression and tone of voice, and includes anxiety, relief, anger, etc.

[0317] "Access to Paid Expert Consultations" is a feature that provides links and procedures for users to receive expert legal assistance or consultations.

[0318] This invention provides a system for responding quickly and accurately to customer inquiries and complaints in a food delivery service. The system includes the following main components:

[0319] System program and processing explanation

[0320] Hardware and Software

[0321] 1. User Device

[0322] Users input questions using devices such as smartphones and tablets, which are equipped with cameras and include functions for facial recognition and voice analysis.

[0323] Technologies used: OpenCV (face recognition), TensorFlow (emotion recognition)

[0324] 2. Server

[0325] The server receives user questions, analyzes them, and generates answers, using spaCy for natural language processing and SQLite as the legal knowledge base.

[0326] Technologies used: Flask (web framework), spaCy (natural language processing), SQLite (database), machine learning model

[0327] Data processing and calculation

[0328] 1. Text input and question analysis

[0329] The user enters a legal question into the terminal and presses the submit button, which sends the entered question in text form to the server.

[0330] The server receives the question and performs text analysis using a natural language processing algorithm (spaCy) to extract key keywords.

[0331] 2. Obtaining legal information

[0332] Based on the extracted keywords, the server queries a legal knowledge base (SQLite) to retrieve relevant legal information, including regulations and laws related to food delivery services.

[0333] 3. Emotion recognition

[0334] The device uses a camera to capture a picture of the user's face in real time and sends the data to a server, which uses OpenCV and TensorFlow to recognize the user's emotional state.

[0335] 4. Answer generation and tone adjustment

[0336] The server uses an AI model to generate an appropriate response based on the legal information acquired and the user's emotional state, adjusting the tone of the response to be gentler if the emotional state is anxious.

[0337] 5. View Answers

[0338] The server generates a response and sends it to the user's device, which displays it to them and, if necessary, provides a link to access legal advice.

[0339] Examples and prompts

[0340] For example, if a user types a question like, "My order hasn't arrived yet, what should I do?" and looks anxious at the camera, the system will generate a response like this:

[0341] "We recommend you check to see if your order arrives soon. Don't worry, our support will be there shortly, just wait a moment."

[0342] In this way, the present invention provides personalized responses based on the user's emotional state, allowing for a fast and accurate response.

[0343] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0344] Step 1:

[0345] User question input

[0346] The user enters a legal question in text format using the device interface and presses the send button. At this time, the input text is stored in a variable called "question." The device also takes a real-time photo of the user's face with a camera and captures video frames for emotion recognition. The data sent is the question text and the video frames.

[0347] Step 2:

[0348] Sending and receiving questions

[0349] The device sends the question text and video frame as an HTTP request to the server. The server receives the request and stores the question text in the analysis variable "question text" and the video frame in the analysis variable "video frame."

[0350] Step 3:

[0351] Question analysis using natural language processing

[0352] The server analyzes the "question text" using a natural language processing algorithm (spaCy) to extract key keywords. The input is the "question text" and the output is the extracted keywords ("keywords"), which are used in subsequent database queries.

[0353] Step 4:

[0354] Submitting queries to the legal knowledge base

[0355] The server sends a query to a legal knowledge base (SQLite database) based on the extracted "keyword group" to retrieve related legal information. The input is the "keyword group" and the output is the related legal information "legal information." The information retrieved from the database includes precedents, regulations, and legal-related data.

[0356] Step 5:

[0357] emotion recognition

[0358] The server analyzes the received "video frames" using OpenCV and TensorFlow to recognize the user's emotional state. The input is the "video frame" and the output is the emotional state "emotional state." The emotional state is classified into categories such as "anxiety," "relief," and "anger."

[0359] Step 6:

[0360] Answer generation and tone control

[0361] The server uses an AI model to generate an appropriate answer based on the acquired "legal information" and "emotional state." If the emotional state is "anxious," it processes the answer by adjusting the tone to be gentler. The input is "legal information" and "emotional state," and the output is the final answer, "Answer."

[0362] Step 7:

[0363] Submitting and viewing answers

[0364] The server sends the generated "answer" to the user's device. The device displays the received answer to the user. If necessary, an access link to a legal expert is also added. The input is the "answer," and the output is the answer and link displayed on the user's screen.

[0365] If a user asks, "My order hasn't arrived yet, what should I do?" and looks anxious, the device will respond with, "We recommend that you check to see if your order is arriving soon. Don't worry, our support will be there shortly, so please wait a moment."

[0366] 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.

[0367] 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.

[0368] 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.

[0369] [Second embodiment]

[0370] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0371] 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.

[0372] 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).

[0373] 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.

[0374] 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.

[0375] 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).

[0376] 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.

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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."

[0382] The present invention is a system for enabling users to obtain quick and accurate answers to legal questions. The operation of this system will now be described in detail.

[0383] First, the user enters their legal question in text format into the terminal. The terminal provides a user interface with a text box for entering the question and a submit button. The user uses this input form to enter their question and then presses the submit button.

[0384] Next, the device sends the user's question to the server in the form of an HTTP request, which the server receives and retrieves the question text.

[0385] The server uses natural language processing algorithms to analyze the text based on the received question. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[0386] Based on these keywords, the server queries a legal knowledge base to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns the appropriate information for the query.

[0387] Based on the acquired information, the server uses an AI model to generate a response. This response contains specific content that is easy for the user to understand. For example, it can be output as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0388] The generated answer is sent from the server to the device, which displays the answer on the user's screen, possibly with links to additional information or relevant legal resources, if necessary.

[0389] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, allowing the user to receive professional assistance.

[0390] Finally, the server collects user feedback and uses it to update the AI ​​model to improve the accuracy of future answers, a process that continuously improves the entire system.

[0391] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content, and is extremely beneficial to users as it allows them to quickly receive expert assistance for even serious legal issues.

[0392] The processing flow will be explained below.

[0393] Step 1:

[0394] An interface is displayed for the user to enter legal questions into the terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[0395] Step 2:

[0396] The device sends the user's question in text format to the server, which sends the question to the server as an HTTP request.

[0397] Step 3:

[0398] The server receives the HTTP request, retrieves the question text, and prepares it for analysis.

[0399] Step 4:

[0400] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[0401] Step 5:

[0402] The server sends a query to a legal knowledge base (database) based on the extracted keywords, where the query is an inquiry to search for relevant legal information.

[0403] Step 6:

[0404] The server retrieves relevant information from a legal knowledge base, which returns relevant legal information, precedents, and legal documents.

[0405] Step 7:

[0406] The server uses an AI model based on the information it acquires to generate specific answers for the user, which are designed to be easy for the user to understand.

[0407] Step 8:

[0408] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[0409] Step 9:

[0410] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[0411] Step 10:

[0412] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[0413] Step 11:

[0414] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[0415] Step 12:

[0416] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[0417] Example 1

[0418] 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."

[0419] There are challenges for users, such as the difficulty of getting fast and accurate answers to legal questions over the Internet, and the difficulty of quickly receiving paid legal assistance when users face serious legal issues. Furthermore, there is a need for the system to effectively utilize user feedback and be continuously improved.

[0420] 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.

[0421] In this invention, the server includes a means for receiving a user's question and analyzing it using a natural language processing algorithm, a means for sending a query to a legal knowledge base based on the extracted keywords to obtain information, and a means for generating an answer using a generative AI model based on the obtained information. This allows users to obtain quick and accurate legal answers, and enables them to quickly receive support from paid legal experts when facing serious legal issues. In addition, by collecting user feedback and updating the generative AI model, the accuracy of the next answer can be improved.

[0422] "User" means any person or entity that utilizes the System to enter legal questions and receive answers.

[0423] A "terminal" is an electronic device through which a user enters legal questions and displays responses from a server.

[0424] A "server" is a central computing device that receives a user's question, analyzes it, generates an answer, and sends it to the terminal.

[0425] A "natural language processing algorithm" is a technology that analyzes text entered by a user and extracts meaning and keywords.

[0426] "Keywords" are important words and phrases extracted from the question entered by the user to identify the meaning of the text.

[0427] A "legal knowledge base" is a database that stores legal information, including copyright law, legal precedents, and regulatory information.

[0428] A "generative AI model" is an artificial intelligence model that generates appropriate answers for users based on information obtained from a legal knowledge base.

[0429] An "answer" is a response message generated by the server in response to a user's question.

[0430] "Feedback" is the user's evaluation or opinion of the system's response.

[0431] A "paid legal consultation" is a paid legal advice service provided by a professional lawyer.

[0432] The present invention is a system for allowing a user to input a legal question and receive a prompt and appropriate answer based on the question, the system including a terminal, a server, and a legal knowledge base.

[0433] First, the user enters a legal question in text format into the device. The device provides a user interface, displaying a text box for entering the question and a submit button. For example, the user enters the question, "Is it legal to use music downloaded from YouTube for personal use?" and presses the submit button. At this time, the device detects the click event of the submit button, obtains the entered question text, and proceeds to the next step.

[0434] The device sends the user's question to the server in the form of an HTTP request. The HTTP request includes the question text. The device then generates an HTTP POST request including the question text and sends the data to the specified endpoint. This establishes network communication and the data reaches the server.

[0435] The server receives the HTTP request and retrieves the question text. It then uses natural language processing algorithms to analyze the text and extract the subject and keywords of the question. For example, if the server receives the question "Is it legal to download music from YouTube for personal use?", it uses a natural language processing library to extract the keywords "YouTube," "download," "personal use," and "legal."

[0436] The server sends a query to a legal knowledge base based on the extracted keywords to retrieve relevant legal information, for example, the server retrieves information about "copyright law" and "personal use" from the legal knowledge base.

[0437] Next, the server uses the generative AI model to generate a response based on the acquired legal information. For example, if the legal information returned is "personal use may be a copyright infringement," the generative AI model uses that information to generate a response such as "downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0438] The generated answer is sent from the server to the device. The device displays the answer received from the server on the user's screen. If necessary, links to additional information or relevant legal resources are also displayed. For example, the device analyzes the received answer text and updates the user interface to display the text. A message is displayed on the screen stating, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0439] Furthermore, if the user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. The user can click on this link to receive professional assistance. For example, the device may display a link on the screen that reads, "If you need more information, you can consult with a legal professional by clicking this link." and the user can click on it.

[0440] Finally, the server collects user feedback and uses it to update the generative AI model to improve the accuracy of future answers. For example, if a user rates the answer as "helpful," the server stores that feedback in a database and periodically uses it as training data for the generative AI model. This allows the entire system to continuously improve, improving the accuracy of future answers.

[0441] Prompt Sentence Examples

[0442] Here is an example prompt:

[0443] "Is it legal to download music from YouTube for personal use?"

[0444] "Is it illegal to post screenshots from a movie on a website?"

[0445] "Can I use free materials I find online for commercial purposes?"

[0446] In this way, users can minimize legal risks and safely use digital content. Furthermore, the entire system is continuously improved by updating the generative AI model based on feedback.

[0447] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0448] Step 1:

[0449] Users enter and submit legal questions.

[0450] What it does: The device provides a text box and a submit button for the user to enter a question. The user enters a question such as "Is it legal to download music from YouTube for personal use?" and presses the submit button.

[0451] Input: Legal question text entered by the user

[0452] Output: Question text collected by the device

[0453] Step 2:

[0454] The device sends the user's question to the server.

[0455] Specific operation: The device generates an HTTP POST request containing the question text and sends it to the server. Network communication is established and the data arrives at the server.

[0456] Input: Question text collected by the device

[0457] Output: An HTTP request containing the question text arrives at the server.

[0458] Step 3:

[0459] The server receives and parses the question text.

[0460] What it does: The server receives an HTTP request, retrieves the question text, and uses a natural language processing algorithm to extract keywords such as "YouTube," "download," "personal," and "legal."

[0461] Input: HTTP request containing the question text

[0462] Output: Extracted keywords

[0463] Step 4:

[0464] The server queries the legal knowledge base to retrieve the information.

[0465] What happens: The server generates a database query using the keywords "copyright law" and "personal use" and performs a search against the legal knowledge base. Relevant legal information is retrieved from the database.

[0466] Input: Extracted keywords

[0467] Output: Information retrieved from the legal knowledge base

[0468] Step 5:

[0469] The server generates an answer using a generative AI model based on the information it obtains.

[0470] Specific operation: The server uses a generative AI model to generate an answer based on the legal information it has obtained. For example, it might generate an answer such as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0471] Input: Information retrieved from the legal knowledge base

[0472] Output: Answer text provided to the user

[0473] Step 6:

[0474] The server sends the generated response to the terminal.

[0475] Specific operation: The server generates an HTTP response containing the answer text and sends it to the device. The data reaches the device via the network.

[0476] Input: Answer text provided to the user

[0477] Output: HTTP response containing the answer text

[0478] Step 7:

[0479] The device displays the answer to the user.

[0480] What happens: The device parses the received response text and updates the user interface, displaying the response text on the screen and, if necessary, providing links to relevant legal resources.

[0481] Input: HTTP response containing the answer text

[0482] Output: The answer text and link that is displayed to the user

[0483] Step 8:

[0484] The device will display a link to access a paid legal consultation (if required).

[0485] What it does: The device displays a link on the screen that says, "For more information, you can contact a legal professional by following this link." The user can click it.

[0486] Input: Expert Consultation Link Needed

[0487] Output: A user-clickable consultation link

[0488] Step 9:

[0489] The server collects feedback and updates the generative AI model.

[0490] What it does: The server collects user feedback, stores it in a database, and periodically uses it as training data for the generative AI model, improving the accuracy of future answers.

[0491] Input: User feedback

[0492] Output: Updated generative AI model and improved answer accuracy

[0493] (Application example 1)

[0494] 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."

[0495] When users of autonomous vehicles encounter legal questions or problems, there is a lack of means to respond quickly and appropriately. In particular, there is a need for a system that can provide real-time answers to legal questions that arise while driving. To solve this problem, a system is needed that allows users to input questions through an intuitive user interface, including voice input, and quickly provides appropriate legal advice.

[0496] 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.

[0497] In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question and analyze the question using a natural language processing algorithm to extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for providing access to paid consultations with legal experts when the user faces a serious legal issue; means for inputting and transmitting the legal question via a user interface in the autonomous vehicle; means for inputting the legal question in voice form using the vehicle's voice input system; and means for providing an answer via the vehicle's touchscreen or voice output system, thereby enabling the user to receive prompt and appropriate legal advice while driving.

[0498] "User interface" means the means of input and output that a user uses to interact with a system, including touchscreens and voice input systems in autonomous vehicles.

[0499] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language, using a series of algorithms including text analysis and keyword extraction.

[0500] A "legal knowledge base" is a database that stores structured legal information, such as copyright law, case law, and regulatory information, and is intended to provide appropriate legal information in response to queries.

[0501] An "AI model" is a mathematical model that uses artificial intelligence technology to generate appropriate outputs for specific inputs, and is responsible for generating answers to legal questions.

[0502] A "voice input system" is a device or technology that allows a user to input instructions into a system through speech, and converts speech into text using speech recognition technology.

[0503] A "touch screen" is an input device that allows users to operate the device by touching the screen, allowing them to intuitively input questions and check answers.

[0504] A "legal advice system" is a set of computer systems that uses technologies such as natural language processing and AI models to provide appropriate advice on legal questions.

[0505] "Feedback" is information provided by users regarding their satisfaction with the system's responses and suggestions for improvement, and is used as data for improving the system.

[0506] "Consultation" means consultation to obtain expert advice on a specific issue, including conversations with paid legal professionals.

[0507] An "autonomous vehicle" is a vehicle that drives automatically using artificial intelligence and various sensors, and is equipped with technology that minimizes human intervention.

[0508] The system of the present invention is a legal advice system installed in an autonomous vehicle, and aims to provide users with prompt and appropriate answers to legal questions that arise while driving. This system operates by combining a user interface, natural language processing, a legal knowledge base, an AI model, and a voice input / output device.

[0509] System configuration

[0510] 1. User Interface:

[0511] It provides a means for users to input legal questions using touchscreens and voice input systems within autonomous vehicles.

[0512] 2. Voice input system:

[0513] It uses the SpeechRecognition library to recognize the user's speech and converts it to text using the Google Speech Recognition API. For example, if a user asks, "I didn't see that road sign just now. Does that mean I'm speeding?", the system will convert that speech to text.

[0514] 3. Data transmission:

[0515] Questions entered in text format via a voice input system or touchscreen are sent from the car's computer to the server in the form of an HTTP request.

[0516] 4. Text Analysis (Natural Language Processing):

[0517] The server analyzes the received question text using a natural language processing algorithm. As a result of the analysis, it extracts key keywords and themes. For example, in response to the question, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[0518] 5. Obtaining information from the legal knowledge base:

[0519] The server then queries a legal knowledge base based on the extracted keywords to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns appropriate information for the query.

[0520] 6. Answer generation by AI model:

[0521] Based on the legal information obtained by the server, an AI model is used to generate a response in a user-friendly format. For example, the output would be something like, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0522] 7. Suggested answers:

[0523] The generated answers are then sent back into the vehicle and presented to the user via the touchscreen or via a voice output system, which uses the pyttsx3 library to play the text aloud.

[0524] 8. Additional options:

[0525] For serious legal issues, a link is also provided to allow for paid consultation with a legal expert using the vehicle's internet connection.

[0526] 9. Feedback collection and system learning:

[0527] The server collects user feedback and uses it as data to improve the accuracy of answers across the entire system, which will improve the accuracy of answers from the next time onwards.

[0528] Specific examples

[0529] As a concrete example, imagine a user asks the following question:

[0530] Question: "I didn't see the road sign just now. Does that count as speeding?"

[0531] Answer: "Even if you don't see the road signs, you still need to obey the speed limit. It may be a legal violation."

[0532] Prompt Sentence Examples

[0533] User question: "I didn't see the road sign just now, does that mean I'm speeding?"

[0534] Keywords: road signs, speeding

[0535] Search for relevant information in a legal knowledge base and generate the answer: "Even if you don't see the road sign, you must obey the speed limit. It may be a legal violation."

[0536] The system of this invention aims to provide quick and appropriate answers to legal questions while driving, allowing users to use self-driving vehicles with peace of mind.

[0537] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0538] Step 1:

[0539] The user enters a legal question.

[0540] Specifically, a user inputs a question using a touchscreen or voice input system in an autonomous vehicle. When using a voice input system, the user verbally states the question, which the SpeechRecognition library converts into text. The input is the user's question, and the output is a text question.

[0541] Step 2:

[0542] The autonomous vehicle's terminal sends the question to the server.

[0543] Specifically, a text question is sent to the server in the form of an HTTP request. The input is the text question, and the output is an HTTP request to the server.

[0544] Step 3:

[0545] The server receives the question and analyzes it using natural language processing algorithms.

[0546] Specifically, the received text is parsed using natural language processing (NLP) algorithms (e.g., spaCy or NLTK libraries) to extract key keywords and intent, where the input is a textual question and the output is the extracted keywords and themes.

[0547] Step 4:

[0548] The server sends a query to a legal knowledge base based on the extracted keywords.

[0549] Specifically, the extracted keywords are used to query a legal knowledge base (database) to retrieve relevant legal information, where the input is the extracted keywords and the output is the legal information as a query result.

[0550] Step 5:

[0551] The server generates answers using an AI model based on the information it obtains.

[0552] Specifically, an AI model (such as GPT-4) is used to generate an answer based on the acquired legal information in a format that is easy for the user to understand. The input is information obtained from the legal knowledge base, and the output is the generated answer.

[0553] Step 6:

[0554] The server generates a response and sends it to the user's device.

[0555] Specifically, the generated answer is sent to the autonomous vehicle's terminal as an HTTP response. The input at this time is the generated answer, and the output is the HTTP response to the terminal.

[0556] Step 7:

[0557] The device displays the answer to the user.

[0558] Specifically, the answer is displayed on a touchscreen, or the answer is played aloud using a voice output system, which uses the pyttsx3 library to convert text to speech, where the input is the answer provided by the server, and the output is the information the user receives visually or audibly.

[0559] Step 8:

[0560] Providing paid legal consultations when users face serious legal issues.

[0561] Specifically, when a user requests additional advice, for example, a link to access a paid consultation is displayed on the touch screen, where the input is the user's request and the output is the link to access the consultation.

[0562] Step 9:

[0563] The server collects user feedback and updates the AI ​​model.

[0564] Specifically, it collects user-provided feedback, analyzes that data, adds it to the AI ​​model's training dataset, and retrains the model to improve answer accuracy in future iterations. The input is the user feedback, and the output is an updated AI model.

[0565] 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.

[0566] The present invention is a system that allows users to get fast and accurate answers to their legal questions. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the tone and content of the answers based on that information.

[0567] First, the user enters their legal question in text format into the terminal. At this time, the terminal displays a user interface, providing a text box for entering the question and a submit button. The user uses this interface to enter the question and presses the "Submit" button.

[0568] Next, the device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with features such as facial recognition and voice analysis, and these emotion engines are used to analyze the user's emotions in real time.

[0569] After the server receives the question, it uses natural language processing algorithms to analyze the text. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server will extract the keywords "YouTube," "download," "personal use," and "legal."

[0570] Based on the extracted keywords, the server sends a query to a legal knowledge base (database) to retrieve relevant legal information. The legal knowledge base includes copyright law, legal precedents, regulatory information, etc., and returns appropriate information for the query.

[0571] Based on the information obtained, the server uses an AI model to generate a response. This response is adjusted taking into account the user's emotional state. For example, if the emotion engine detects that the user is anxious, the server will create a response in a gentler, more reassuring tone. For example, it might say, "Downloading music from YouTube for personal use may be a copyright infringement. If you are concerned, we recommend obtaining permission from the copyright holder."

[0572] The generated answer is sent from the server to the device, which displays the answer on the user's screen, along with links to additional information and relevant legal resources, if necessary.

[0573] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, which will take the user through the process of obtaining professional assistance.

[0574] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[0575] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content. It also takes into account the user's emotional state to provide more personalized and friendly answers. This is extremely beneficial for users, as they can quickly receive expert assistance even for serious legal issues.

[0576] The processing flow will be explained below.

[0577] Step 1:

[0578] The user operates an interface for entering legal questions into a terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[0579] Step 2:

[0580] The device asks the user questions and uses facial recognition and voice analysis to collect emotional data, analyzing the user's emotional state (e.g., anxiety, anger, excitement, etc.) from their facial expressions and voice tone.

[0581] Step 3:

[0582] The device sends the user's question text and emotion data to the server in the form of an HTTP request.

[0583] Step 4:

[0584] The server receives the HTTP request and retrieves the question text and emotion data.

[0585] Step 5:

[0586] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[0587] Step 6:

[0588] The server sends a query to a legal knowledge base (database) based on the extracted keywords to search for relevant legal information.

[0589] Step 7:

[0590] The server retrieves relevant information from a legal knowledge base, returning legal information, precedents, legal documents, etc.

[0591] Step 8:

[0592] The server uses an AI model to generate a response based on the information acquired and the user's emotional data. The tone and content of the response are adjusted according to the emotional data. For example, if the user is anxious, the response will be generated in a gentler tone.

[0593] Step 9:

[0594] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[0595] Step 10:

[0596] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[0597] Step 11:

[0598] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[0599] Step 12:

[0600] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[0601] Step 13:

[0602] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[0603] Example 2

[0604] 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."

[0605] Previously, when users had legal questions, it was difficult to get a quick and accurate answer, and it was not possible to respond appropriately based on the user's emotional state. Furthermore, when users faced serious legal issues, it was difficult to receive appropriate support because there was no way to quickly access paid legal experts.

[0606] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for a terminal to analyze the user's emotions; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using a generative AI model based on the information obtained; means for the server to adjust the answer generated by the server based on the user's emotional state; means for the server to send the answer generated by the server to the user's terminal and for the terminal to display the answer to the user; and means for providing access to paid consultations with legal experts when the user faces a serious legal problem. This allows users to receive prompt and accurate legal advice and personalized responses according to their emotional state. It also allows users to receive prompt expert support even for serious legal issues.

[0607] "User" means any person who uses the System to enter legal questions and receive answers.

[0608] "Terminal" means the electronic device used by a User to enter legal questions and view answers.

[0609] "Emotion analysis" refers to the technology and process by which a device detects and analyzes a user's emotional state.

[0610] "Server" refers to the central processing system for processing legal inquiries received from Users, generating answers, and returning them to Users.

[0611] A "natural language processing algorithm" refers to an algorithm that analyzes text questions and extracts keywords and intent.

[0612] "Keywords" refer to important words or phrases extracted from a user's question.

[0613] A "legal knowledge base" refers to a database that stores legal information (e.g., laws, precedents, regulatory information, etc.).

[0614] "Query" refers to a search instruction sent by a server to a legal knowledge base.

[0615] "Generative AI model" refers to an artificial intelligence model that generates answers based on acquired legal information.

[0616] "Answer" refers to the response provided by the server to the user's question using a generative AI model.

[0617] "Feedback" refers to ratings and comments on system responses collected from users.

[0618] "Paid legal consultation" means legal consultation services provided for a fee.

[0619] "Access Link" means a connection that directs a user to a paid consultation with a legal professional.

[0620] "Tuning" refers to the process of changing the tone and content of the generated answers depending on the user's emotional state.

[0621] This invention is a system that allows users to quickly and accurately obtain answers to legal questions. Furthermore, it provides personalized responses by incorporating an emotion engine that recognizes the user's emotions and adjusts the tone and content of the response based on that information. To effectively implement this system, the following hardware and software are required:

[0622] First, the user enters their legal question in text format into the device. At this time, a user interface is displayed on the device, providing a text box for entering the question and a submit button. The user uses this interface to enter their question and presses the "Submit" button. An example of a question that a user might enter is, "Is it okay to watch a movie I downloaded online with my friends?"

[0623] The device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with a facial recognition camera and a voice analysis microphone, and these are used to analyze the user's emotions in real time using an emotion engine. Emotion analysis determines, for example, whether the user is feeling anxious based on their facial expressions and tone of voice when entering a question.

[0624] After the server receives the question, it performs text analysis using natural language processing algorithms (e.g., SpaCy or NLTK). This analysis extracts topics and keywords from the question. For example, if a user asks, "Is it okay to watch a movie I downloaded online with my friends?", the server extracts the keywords "online," "download," "movie," "watch with friends," and "okay."

[0625] Next, the server sends a query to a legal knowledge base (e.g., a database built with SQL) based on the extracted keywords to retrieve relevant legal information. The legal knowledge base stores copyright law, precedents, regulatory information, and other information, and returns appropriate information in response to the query. Based on the information retrieved by the server, a generative AI model (e.g., GPT-3) is used to generate an answer to the user's question.

[0626] The generated answer is adjusted to take into account the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server will create a gentler, more reassuring tone of response, such as, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[0627] The server then sends the generated answer to the device, which then displays it on the user's screen. The answer may also include links to additional information and related legal resources. Additionally, if the user faces a serious legal problem, the device may display a link to access a paid legal consultation. Clicking on this link will take the user through the process of obtaining professional assistance.

[0628] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[0629] Examples of prompts:

[0630] "Is it legal to watch movies downloaded online with friends?"

[0631] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0632] Step 1:

[0633] The user enters a legal question in text format using the device's user interface and presses the "Submit" button. This obtains the legal question as input from the end user. An example of a specific prompt sentence is "Is it okay to watch a movie downloaded online with a friend?"

[0634] Step 2:

[0635] The device receives the text entered by the user and analyzes the user's emotions in real time using a facial recognition camera and a voice analysis microphone. The emotion analysis engine determines the user's emotional state from their facial expressions and tone of voice. The results of this analysis (e.g., the user is anxious) are used as input for the next step.

[0636] Step 3:

[0637] The device sends the user's question and the emotion analysis results to the server in the form of an HTTP request. The server receives this request and obtains the input text and emotion data. As a result, the server obtains the user's question and information about their emotional state as input.

[0638] Step 4:

[0639] The server analyzes the received question text using a natural language processing algorithm (e.g., SpaCy or NLTK). During this analysis, themes and keywords are extracted from the question. For example, keywords such as "online," "download," "movie," "watch with friends," and "okay" are extracted and used as input for the next step.

[0640] Step 5:

[0641] The server sends a query to a legal knowledge base (e.g., an SQL database) based on the extracted keywords, which searches for relevant legal information (e.g., copyright law, legal precedents, regulatory information, etc.) and obtains the information obtained from the query as output.

[0642] Step 6:

[0643] The server uses a generative AI model (e.g., GPT-3) to generate an answer based on the legal information it obtains. The answer is adjusted based on the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server might generate a gentle answer saying, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[0644] Step 7:

[0645] The server generates a response and sends it to the user's device. The device receives the response and displays it on the user's screen. This allows the user to obtain legal advice through their device. Links to relevant legal resources are also displayed, if necessary.

[0646] Step 8:

[0647] If a user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. For example, a link such as "Click here for more information" will be displayed, and the user can click it to begin the process of receiving professional assistance.

[0648] Step 9:

[0649] The server collects user feedback. User ratings and comments are collected and stored in a database. The server analyzes this feedback and updates the generative AI model to improve the accuracy of future answers. This process continuously improves the entire system.

[0650] (Application example 2)

[0651] 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."

[0652] For food delivery services, responding quickly and accurately to customer questions and complaints is crucial to maintaining customer satisfaction. However, previous systems struggled to generate personalized responses that took into account the user's emotional state. They also lacked the means to quickly provide appropriate legal information and expert assistance. This sometimes resulted in delayed responses to user complaints, leading to lower customer satisfaction.

[0653] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for the terminal to recognize the user's emotional state using facial recognition and voice analysis; means for the server to adjust the tone of the answer based on the recognized emotional state; and means for providing access to paid expert consultations when the user faces a serious legal problem. This enables personalized answers to be provided based on the user's emotional state and rapid provision of legal information and expert assistance.

[0654] A "means for users to enter legal questions" is a system that provides an interface, text box, and submit button for users to enter legal questions in text format using a terminal.

[0655] A "natural language processing algorithm" is a machine learning algorithm for understanding, analyzing, and processing human language, and is a technology used to extract keywords and intent from text data.

[0656] A "legal knowledge base" is a database that stores legal information and data, including copyright law, legal precedents, and regulatory information.

[0657] An "AI model" is an artificial intelligence model trained by machine learning algorithms and used to generate appropriate answers based on input data.

[0658] "Facial recognition" is a technology that uses image processing technology to detect a user's face and analyze their facial expressions and features.

[0659] "Voice analysis" is a technology that analyzes voice data and recognizes the user's tone of voice and emotions.

[0660] "Emotional state" refers to a psychological state inferred from a user's facial expression and tone of voice, and includes anxiety, relief, anger, etc.

[0661] "Access to Paid Expert Consultations" is a feature that provides links and procedures for users to receive expert legal assistance or consultations.

[0662] This invention provides a system for responding quickly and accurately to customer inquiries and complaints in a food delivery service. The system includes the following main components:

[0663] System program and processing explanation

[0664] Hardware and Software

[0665] 1. User Device

[0666] Users input questions using devices such as smartphones and tablets, which are equipped with cameras and include functions for facial recognition and voice analysis.

[0667] Technologies used: OpenCV (face recognition), TensorFlow (emotion recognition)

[0668] 2. Server

[0669] The server receives user questions, analyzes them, and generates answers, using spaCy for natural language processing and SQLite as the legal knowledge base.

[0670] Technologies used: Flask (web framework), spaCy (natural language processing), SQLite (database), machine learning model

[0671] Data processing and calculation

[0672] 1. Text input and question analysis

[0673] The user enters a legal question into the terminal and presses the submit button, which sends the entered question in text form to the server.

[0674] The server receives the question and performs text analysis using a natural language processing algorithm (spaCy) to extract key keywords.

[0675] 2. Obtaining legal information

[0676] Based on the extracted keywords, the server queries a legal knowledge base (SQLite) to retrieve relevant legal information, including regulations and laws related to food delivery services.

[0677] 3. Emotion recognition

[0678] The device uses a camera to capture a picture of the user's face in real time and sends the data to a server, which uses OpenCV and TensorFlow to recognize the user's emotional state.

[0679] 4. Answer generation and tone adjustment

[0680] The server uses an AI model to generate an appropriate response based on the legal information acquired and the user's emotional state, adjusting the tone of the response to be gentler if the emotional state is anxious.

[0681] 5. View Answers

[0682] The server generates a response and sends it to the user's device, which displays it to them and, if necessary, provides a link to access legal advice.

[0683] Examples and prompts

[0684] For example, if a user types a question like, "My order hasn't arrived yet, what should I do?" and looks anxious at the camera, the system will generate a response like this:

[0685] "We recommend you check to see if your order arrives soon. Don't worry, our support will be there shortly, just wait a moment."

[0686] In this way, the present invention provides personalized responses based on the user's emotional state, allowing for a fast and accurate response.

[0687] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0688] Step 1:

[0689] User question input

[0690] The user enters a legal question in text format using the device interface and presses the send button. At this time, the input text is stored in a variable called "question." The device also takes a real-time photo of the user's face with a camera and captures video frames for emotion recognition. The data sent is the question text and the video frames.

[0691] Step 2:

[0692] Sending and receiving questions

[0693] The device sends the question text and video frame as an HTTP request to the server. The server receives the request and stores the question text in the analysis variable "question text" and the video frame in the analysis variable "video frame."

[0694] Step 3:

[0695] Question analysis using natural language processing

[0696] The server analyzes the "question text" using a natural language processing algorithm (spaCy) to extract key keywords. The input is the "question text" and the output is the extracted keywords ("keywords"), which are used in subsequent database queries.

[0697] Step 4:

[0698] Submitting queries to the legal knowledge base

[0699] The server sends a query to a legal knowledge base (SQLite database) based on the extracted "keyword group" to retrieve related legal information. The input is the "keyword group" and the output is the related legal information "legal information." The information retrieved from the database includes precedents, regulations, and legal-related data.

[0700] Step 5:

[0701] emotion recognition

[0702] The server analyzes the received "video frames" using OpenCV and TensorFlow to recognize the user's emotional state. The input is the "video frame" and the output is the emotional state "emotional state." The emotional state is classified into categories such as "anxiety," "relief," and "anger."

[0703] Step 6:

[0704] Answer generation and tone control

[0705] The server uses an AI model to generate an appropriate answer based on the acquired "legal information" and "emotional state." If the emotional state is "anxious," it processes the answer by adjusting the tone to be gentler. The input is "legal information" and "emotional state," and the output is the final answer, "Answer."

[0706] Step 7:

[0707] Submitting and viewing answers

[0708] The server sends the generated "answer" to the user's device. The device displays the received answer to the user. If necessary, an access link to a legal expert is also added. The input is the "answer," and the output is the answer and link displayed on the user's screen.

[0709] If a user asks, "My order hasn't arrived yet, what should I do?" and looks anxious, the device will respond with, "We recommend that you check to see if your order is arriving soon. Don't worry, our support will be there shortly, so please wait a moment."

[0710] 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.

[0711] 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.

[0712] 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.

[0713] [Third embodiment]

[0714] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0715] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0716] 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).

[0717] 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.

[0718] 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.

[0719] 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).

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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."

[0726] The present invention is a system for enabling users to obtain quick and accurate answers to legal questions. The operation of this system will now be described in detail.

[0727] First, the user enters their legal question in text format into the terminal. The terminal provides a user interface with a text box for entering the question and a submit button. The user uses this input form to enter their question and then presses the submit button.

[0728] Next, the device sends the user's question to the server in the form of an HTTP request, which the server receives and retrieves the question text.

[0729] The server uses natural language processing algorithms to analyze the text based on the received question. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[0730] Based on these keywords, the server queries a legal knowledge base to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns the appropriate information for the query.

[0731] Based on the acquired information, the server uses an AI model to generate a response. This response contains specific content that is easy for the user to understand. For example, it can be output as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0732] The generated answer is sent from the server to the device, which displays the answer on the user's screen, possibly with links to additional information or relevant legal resources, if necessary.

[0733] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, allowing the user to receive professional assistance.

[0734] Finally, the server collects user feedback and uses it to update the AI ​​model to improve the accuracy of future answers, a process that continuously improves the entire system.

[0735] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content, and is extremely beneficial to users as it allows them to quickly receive expert assistance for even serious legal issues.

[0736] The processing flow will be explained below.

[0737] Step 1:

[0738] An interface is displayed for the user to enter legal questions into the terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[0739] Step 2:

[0740] The device sends the user's question in text format to the server, which sends the question to the server as an HTTP request.

[0741] Step 3:

[0742] The server receives the HTTP request, retrieves the question text, and prepares it for analysis.

[0743] Step 4:

[0744] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[0745] Step 5:

[0746] The server sends a query to a legal knowledge base (database) based on the extracted keywords, where the query is an inquiry to search for relevant legal information.

[0747] Step 6:

[0748] The server retrieves relevant information from a legal knowledge base, which returns relevant legal information, precedents, and legal documents.

[0749] Step 7:

[0750] The server uses an AI model based on the information it acquires to generate specific answers for the user, which are designed to be easy for the user to understand.

[0751] Step 8:

[0752] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[0753] Step 9:

[0754] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[0755] Step 10:

[0756] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[0757] Step 11:

[0758] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[0759] Step 12:

[0760] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[0761] Example 1

[0762] 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."

[0763] There are challenges for users, such as the difficulty of getting fast and accurate answers to legal questions over the Internet, and the difficulty of quickly receiving paid legal assistance when users face serious legal issues. Furthermore, there is a need for the system to effectively utilize user feedback and be continuously improved.

[0764] 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.

[0765] In this invention, the server includes a means for receiving a user's question and analyzing it using a natural language processing algorithm, a means for sending a query to a legal knowledge base based on the extracted keywords to obtain information, and a means for generating an answer using a generative AI model based on the obtained information. This allows users to obtain quick and accurate legal answers, and enables them to quickly receive support from paid legal experts when facing serious legal issues. In addition, by collecting user feedback and updating the generative AI model, the accuracy of the next answer can be improved.

[0766] "User" means any person or entity that utilizes the System to enter legal questions and receive answers.

[0767] A "terminal" is an electronic device through which a user enters legal questions and displays responses from a server.

[0768] A "server" is a central computing device that receives a user's question, analyzes it, generates an answer, and sends it to the terminal.

[0769] A "natural language processing algorithm" is a technology that analyzes text entered by a user and extracts meaning and keywords.

[0770] "Keywords" are important words and phrases extracted from the question entered by the user to identify the meaning of the text.

[0771] A "legal knowledge base" is a database that stores legal information, including copyright law, legal precedents, and regulatory information.

[0772] A "generative AI model" is an artificial intelligence model that generates appropriate answers for users based on information obtained from a legal knowledge base.

[0773] An "answer" is a response message generated by the server in response to a user's question.

[0774] "Feedback" is the user's evaluation or opinion of the system's response.

[0775] A "paid legal consultation" is a paid legal advice service provided by a professional lawyer.

[0776] The present invention is a system for allowing a user to input a legal question and receive a prompt and appropriate answer based on the question, the system including a terminal, a server, and a legal knowledge base.

[0777] First, the user enters a legal question in text format into the device. The device provides a user interface, displaying a text box for entering the question and a submit button. For example, the user enters the question, "Is it legal to use music downloaded from YouTube for personal use?" and presses the submit button. At this time, the device detects the click event of the submit button, obtains the entered question text, and proceeds to the next step.

[0778] The device sends the user's question to the server in the form of an HTTP request. The HTTP request includes the question text. The device then generates an HTTP POST request including the question text and sends the data to the specified endpoint. This establishes network communication and the data reaches the server.

[0779] The server receives the HTTP request and retrieves the question text. It then uses natural language processing algorithms to analyze the text and extract the subject and keywords of the question. For example, if the server receives the question "Is it legal to download music from YouTube for personal use?", it uses a natural language processing library to extract the keywords "YouTube," "download," "personal use," and "legal."

[0780] The server sends a query to a legal knowledge base based on the extracted keywords to retrieve relevant legal information, for example, the server retrieves information about "copyright law" and "personal use" from the legal knowledge base.

[0781] Next, the server uses the generative AI model to generate a response based on the acquired legal information. For example, if the legal information returned is "personal use may be a copyright infringement," the generative AI model uses that information to generate a response such as "downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0782] The generated answer is sent from the server to the device. The device displays the answer received from the server on the user's screen. If necessary, links to additional information or relevant legal resources are also displayed. For example, the device analyzes the received answer text and updates the user interface to display the text. A message is displayed on the screen stating, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0783] Furthermore, if the user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. The user can click on this link to receive professional assistance. For example, the device may display a link on the screen that reads, "If you need more information, you can consult with a legal professional by clicking this link." and the user can click on it.

[0784] Finally, the server collects user feedback and uses it to update the generative AI model to improve the accuracy of future answers. For example, if a user rates the answer as "helpful," the server stores that feedback in a database and periodically uses it as training data for the generative AI model. This allows the entire system to continuously improve, improving the accuracy of future answers.

[0785] Prompt Sentence Examples

[0786] Here is an example prompt:

[0787] "Is it legal to download music from YouTube for personal use?"

[0788] "Is it illegal to post screenshots from a movie on a website?"

[0789] "Can I use free materials I find online for commercial purposes?"

[0790] In this way, users can minimize legal risks and safely use digital content. Furthermore, the entire system is continuously improved by updating the generative AI model based on feedback.

[0791] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0792] Step 1:

[0793] Users enter and submit legal questions.

[0794] What it does: The device provides a text box and a submit button for the user to enter a question. The user enters a question such as "Is it legal to download music from YouTube for personal use?" and presses the submit button.

[0795] Input: Legal question text entered by the user

[0796] Output: Question text collected by the device

[0797] Step 2:

[0798] The device sends the user's question to the server.

[0799] Specific operation: The device generates an HTTP POST request containing the question text and sends it to the server. Network communication is established and the data arrives at the server.

[0800] Input: Question text collected by the device

[0801] Output: An HTTP request containing the question text arrives at the server.

[0802] Step 3:

[0803] The server receives and parses the question text.

[0804] What it does: The server receives an HTTP request, retrieves the question text, and uses a natural language processing algorithm to extract keywords such as "YouTube," "download," "personal," and "legal."

[0805] Input: HTTP request containing the question text

[0806] Output: Extracted keywords

[0807] Step 4:

[0808] The server queries the legal knowledge base to retrieve the information.

[0809] What happens: The server generates a database query using the keywords "copyright law" and "personal use" and performs a search against the legal knowledge base. Relevant legal information is retrieved from the database.

[0810] Input: Extracted keywords

[0811] Output: Information retrieved from the legal knowledge base

[0812] Step 5:

[0813] The server generates an answer using a generative AI model based on the information it obtains.

[0814] Specific operation: The server uses a generative AI model to generate an answer based on the legal information it has obtained. For example, it might generate an answer such as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0815] Input: Information retrieved from the legal knowledge base

[0816] Output: Answer text provided to the user

[0817] Step 6:

[0818] The server sends the generated response to the terminal.

[0819] Specific operation: The server generates an HTTP response containing the answer text and sends it to the device. The data reaches the device via the network.

[0820] Input: Answer text provided to the user

[0821] Output: HTTP response containing the answer text

[0822] Step 7:

[0823] The device displays the answer to the user.

[0824] What happens: The device parses the received response text and updates the user interface, displaying the response text on the screen and, if necessary, providing links to relevant legal resources.

[0825] Input: HTTP response containing the answer text

[0826] Output: The answer text and link that is displayed to the user

[0827] Step 8:

[0828] The device will display a link to access a paid legal consultation (if required).

[0829] What it does: The device displays a link on the screen that says, "For more information, you can contact a legal professional by following this link." The user can click it.

[0830] Input: Expert Consultation Link Needed

[0831] Output: A user-clickable consultation link

[0832] Step 9:

[0833] The server collects feedback and updates the generative AI model.

[0834] What it does: The server collects user feedback, stores it in a database, and periodically uses it as training data for the generative AI model, improving the accuracy of future answers.

[0835] Input: User feedback

[0836] Output: Updated generative AI model and improved answer accuracy

[0837] (Application example 1)

[0838] 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."

[0839] When users of autonomous vehicles encounter legal questions or problems, there is a lack of means to respond quickly and appropriately. In particular, there is a need for a system that can provide real-time answers to legal questions that arise while driving. To solve this problem, a system is needed that allows users to input questions through an intuitive user interface, including voice input, and quickly provides appropriate legal advice.

[0840] 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.

[0841] In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question and analyze the question using a natural language processing algorithm to extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for providing access to paid consultations with legal experts when the user faces a serious legal issue; means for inputting and transmitting the legal question via a user interface in the autonomous vehicle; means for inputting the legal question in voice form using the vehicle's voice input system; and means for providing an answer via the vehicle's touchscreen or voice output system, thereby enabling the user to receive prompt and appropriate legal advice while driving.

[0842] "User interface" means the means of input and output that a user uses to interact with a system, including touchscreens and voice input systems in autonomous vehicles.

[0843] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language, using a series of algorithms including text analysis and keyword extraction.

[0844] A "legal knowledge base" is a database that stores structured legal information, such as copyright law, case law, and regulatory information, and is intended to provide appropriate legal information in response to queries.

[0845] An "AI model" is a mathematical model that uses artificial intelligence technology to generate appropriate outputs for specific inputs, and is responsible for generating answers to legal questions.

[0846] A "voice input system" is a device or technology that allows a user to input instructions into a system through speech, and converts speech into text using speech recognition technology.

[0847] A "touch screen" is an input device that allows users to operate the device by touching the screen, allowing them to intuitively input questions and check answers.

[0848] A "legal advice system" is a set of computer systems that uses technologies such as natural language processing and AI models to provide appropriate advice on legal questions.

[0849] "Feedback" is information provided by users regarding their satisfaction with the system's responses and suggestions for improvement, and is used as data for improving the system.

[0850] "Consultation" means consultation to obtain expert advice on a specific issue, including conversations with paid legal professionals.

[0851] An "autonomous vehicle" is a vehicle that drives automatically using artificial intelligence and various sensors, and is equipped with technology that minimizes human intervention.

[0852] The system of the present invention is a legal advice system installed in an autonomous vehicle, and aims to provide users with prompt and appropriate answers to legal questions that arise while driving. This system operates by combining a user interface, natural language processing, a legal knowledge base, an AI model, and a voice input / output device.

[0853] System configuration

[0854] 1. User Interface:

[0855] It provides a means for users to input legal questions using touchscreens and voice input systems within autonomous vehicles.

[0856] 2. Voice input system:

[0857] It uses the SpeechRecognition library to recognize the user's speech and converts it to text using the Google Speech Recognition API. For example, if a user asks, "I didn't see that road sign just now. Does that mean I'm speeding?", the system will convert that speech to text.

[0858] 3. Data transmission:

[0859] Questions entered in text format via a voice input system or touchscreen are sent from the car's computer to the server in the form of an HTTP request.

[0860] 4. Text Analysis (Natural Language Processing):

[0861] The server analyzes the received question text using a natural language processing algorithm. As a result of the analysis, it extracts key keywords and themes. For example, in response to the question, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[0862] 5. Obtaining information from the legal knowledge base:

[0863] The server then queries a legal knowledge base based on the extracted keywords to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns appropriate information for the query.

[0864] 6. Answer generation by AI model:

[0865] Based on the legal information obtained by the server, an AI model is used to generate a response in a user-friendly format. For example, the output would be something like, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[0866] 7. Suggested answers:

[0867] The generated answers are then sent back into the vehicle and presented to the user via the touchscreen or via a voice output system, which uses the pyttsx3 library to play the text aloud.

[0868] 8. Additional options:

[0869] For serious legal issues, a link is also provided to allow for paid consultation with a legal expert using the vehicle's internet connection.

[0870] 9. Feedback collection and system learning:

[0871] The server collects user feedback and uses it as data to improve the accuracy of answers across the entire system, which will improve the accuracy of answers from the next time onwards.

[0872] Specific examples

[0873] As a concrete example, imagine a user asks the following question:

[0874] Question: "I didn't see the road sign just now. Does that count as speeding?"

[0875] Answer: "Even if you don't see the road signs, you still need to obey the speed limit. It may be a legal violation."

[0876] Prompt Sentence Examples

[0877] User question: "I didn't see the road sign just now, does that mean I'm speeding?"

[0878] Keywords: road signs, speeding

[0879] Search for relevant information in a legal knowledge base and generate the answer: "Even if you don't see the road sign, you must obey the speed limit. It may be a legal violation."

[0880] The system of this invention aims to provide quick and appropriate answers to legal questions while driving, allowing users to use self-driving vehicles with peace of mind.

[0881] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0882] Step 1:

[0883] The user enters a legal question.

[0884] Specifically, a user inputs a question using a touchscreen or voice input system in an autonomous vehicle. When using a voice input system, the user verbally states the question, which the SpeechRecognition library converts into text. The input is the user's question, and the output is a text question.

[0885] Step 2:

[0886] The autonomous vehicle's terminal sends the question to the server.

[0887] Specifically, a text question is sent to the server in the form of an HTTP request. The input is the text question, and the output is an HTTP request to the server.

[0888] Step 3:

[0889] The server receives the question and analyzes it using natural language processing algorithms.

[0890] Specifically, the received text is parsed using natural language processing (NLP) algorithms (e.g., spaCy or NLTK libraries) to extract key keywords and intent, where the input is a textual question and the output is the extracted keywords and themes.

[0891] Step 4:

[0892] The server sends a query to a legal knowledge base based on the extracted keywords.

[0893] Specifically, the extracted keywords are used to query a legal knowledge base (database) to retrieve relevant legal information, where the input is the extracted keywords and the output is the legal information as a query result.

[0894] Step 5:

[0895] The server generates answers using an AI model based on the information it obtains.

[0896] Specifically, an AI model (such as GPT-4) is used to generate an answer based on the acquired legal information in a format that is easy for the user to understand. The input is information obtained from the legal knowledge base, and the output is the generated answer.

[0897] Step 6:

[0898] The server generates a response and sends it to the user's device.

[0899] Specifically, the generated answer is sent to the autonomous vehicle's terminal as an HTTP response. The input at this time is the generated answer, and the output is the HTTP response to the terminal.

[0900] Step 7:

[0901] The device displays the answer to the user.

[0902] Specifically, the answer is displayed on a touchscreen, or the answer is played aloud using a voice output system, which uses the pyttsx3 library to convert text to speech, where the input is the answer provided by the server, and the output is the information the user receives visually or audibly.

[0903] Step 8:

[0904] Providing paid legal consultations when users face serious legal issues.

[0905] Specifically, when a user requests additional advice, for example, a link to access a paid consultation is displayed on the touch screen, where the input is the user's request and the output is the link to access the consultation.

[0906] Step 9:

[0907] The server collects user feedback and updates the AI ​​model.

[0908] Specifically, it collects user-provided feedback, analyzes that data, adds it to the AI ​​model's training dataset, and retrains the model to improve answer accuracy in future iterations. The input is the user feedback, and the output is an updated AI model.

[0909] 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.

[0910] The present invention is a system that allows users to get fast and accurate answers to their legal questions. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the tone and content of the answers based on that information.

[0911] First, the user enters their legal question in text format into the terminal. At this time, the terminal displays a user interface, providing a text box for entering the question and a submit button. The user uses this interface to enter the question and presses the "Submit" button.

[0912] Next, the device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with features such as facial recognition and voice analysis, and these emotion engines are used to analyze the user's emotions in real time.

[0913] After the server receives the question, it uses natural language processing algorithms to analyze the text. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server will extract the keywords "YouTube," "download," "personal use," and "legal."

[0914] Based on the extracted keywords, the server sends a query to a legal knowledge base (database) to retrieve relevant legal information. The legal knowledge base includes copyright law, legal precedents, regulatory information, etc., and returns appropriate information for the query.

[0915] Based on the information obtained, the server uses an AI model to generate a response. This response is adjusted taking into account the user's emotional state. For example, if the emotion engine detects that the user is anxious, the server will create a response in a gentler, more reassuring tone. For example, it might say, "Downloading music from YouTube for personal use may be a copyright infringement. If you are concerned, we recommend obtaining permission from the copyright holder."

[0916] The generated answer is sent from the server to the device, which displays the answer on the user's screen, along with links to additional information and relevant legal resources, if necessary.

[0917] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, which will take the user through the process of obtaining professional assistance.

[0918] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[0919] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content. It also takes into account the user's emotional state to provide more personalized and friendly answers. This is extremely beneficial for users, as they can quickly receive expert assistance even for serious legal issues.

[0920] The processing flow will be explained below.

[0921] Step 1:

[0922] The user operates an interface for entering legal questions into a terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[0923] Step 2:

[0924] The device asks the user questions and uses facial recognition and voice analysis to collect emotional data, analyzing the user's emotional state (e.g., anxiety, anger, excitement, etc.) from their facial expressions and voice tone.

[0925] Step 3:

[0926] The device sends the user's question text and emotion data to the server in the form of an HTTP request.

[0927] Step 4:

[0928] The server receives the HTTP request and retrieves the question text and emotion data.

[0929] Step 5:

[0930] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[0931] Step 6:

[0932] The server sends a query to a legal knowledge base (database) based on the extracted keywords to search for relevant legal information.

[0933] Step 7:

[0934] The server retrieves relevant information from a legal knowledge base, returning legal information, precedents, legal documents, etc.

[0935] Step 8:

[0936] The server uses an AI model to generate a response based on the information acquired and the user's emotional data. The tone and content of the response are adjusted according to the emotional data. For example, if the user is anxious, the response will be generated in a gentler tone.

[0937] Step 9:

[0938] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[0939] Step 10:

[0940] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[0941] Step 11:

[0942] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[0943] Step 12:

[0944] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[0945] Step 13:

[0946] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[0947] Example 2

[0948] 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."

[0949] Previously, when users had legal questions, it was difficult to get a quick and accurate answer, and it was not possible to respond appropriately based on the user's emotional state. Furthermore, when users faced serious legal issues, it was difficult to receive appropriate support because there was no way to quickly access paid legal experts.

[0950] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for a terminal to analyze the user's emotions; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using a generative AI model based on the information obtained; means for the server to adjust the answer generated by the server based on the user's emotional state; means for the server to send the answer generated by the server to the user's terminal and for the terminal to display the answer to the user; and means for providing access to paid consultations with legal experts when the user faces a serious legal problem. This allows users to receive prompt and accurate legal advice and personalized responses according to their emotional state. It also allows users to receive prompt expert support even for serious legal issues.

[0951] "User" means any person who uses the System to enter legal questions and receive answers.

[0952] "Terminal" means the electronic device used by a User to enter legal questions and view answers.

[0953] "Emotion analysis" refers to the technology and process by which a device detects and analyzes a user's emotional state.

[0954] "Server" refers to the central processing system for processing legal inquiries received from Users, generating answers, and returning them to Users.

[0955] A "natural language processing algorithm" refers to an algorithm that analyzes text questions and extracts keywords and intent.

[0956] "Keywords" refer to important words or phrases extracted from a user's question.

[0957] A "legal knowledge base" refers to a database that stores legal information (e.g., laws, precedents, regulatory information, etc.).

[0958] "Query" refers to a search instruction sent by a server to a legal knowledge base.

[0959] "Generative AI model" refers to an artificial intelligence model that generates answers based on acquired legal information.

[0960] "Answer" refers to the response provided by the server to the user's question using a generative AI model.

[0961] "Feedback" refers to ratings and comments on system responses collected from users.

[0962] "Paid legal consultation" means legal consultation services provided for a fee.

[0963] "Access Link" means a connection that directs a user to a paid consultation with a legal professional.

[0964] "Tuning" refers to the process of changing the tone and content of the generated answers depending on the user's emotional state.

[0965] This invention is a system that allows users to quickly and accurately obtain answers to legal questions. Furthermore, it provides personalized responses by incorporating an emotion engine that recognizes the user's emotions and adjusts the tone and content of the response based on that information. To effectively implement this system, the following hardware and software are required:

[0966] First, the user enters their legal question in text format into the device. At this time, a user interface is displayed on the device, providing a text box for entering the question and a submit button. The user uses this interface to enter their question and presses the "Submit" button. An example of a question that a user might enter is, "Is it okay to watch a movie I downloaded online with my friends?"

[0967] The device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with a facial recognition camera and a voice analysis microphone, and these are used to analyze the user's emotions in real time using an emotion engine. Emotion analysis determines, for example, whether the user is feeling anxious based on their facial expressions and tone of voice when entering a question.

[0968] After the server receives the question, it performs text analysis using natural language processing algorithms (e.g., SpaCy or NLTK). This analysis extracts topics and keywords from the question. For example, if a user asks, "Is it okay to watch a movie I downloaded online with my friends?", the server extracts the keywords "online," "download," "movie," "watch with friends," and "okay."

[0969] Next, the server sends a query to a legal knowledge base (e.g., a database built with SQL) based on the extracted keywords to retrieve relevant legal information. The legal knowledge base stores copyright law, precedents, regulatory information, and other information, and returns appropriate information in response to the query. Based on the information retrieved by the server, a generative AI model (e.g., GPT-3) is used to generate an answer to the user's question.

[0970] The generated answer is adjusted to take into account the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server will create a gentler, more reassuring tone of response, such as, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[0971] The server then sends the generated answer to the device, which then displays it on the user's screen. The answer may also include links to additional information and related legal resources. Additionally, if the user faces a serious legal problem, the device may display a link to access a paid legal consultation. Clicking on this link will take the user through the process of obtaining professional assistance.

[0972] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[0973] Examples of prompts:

[0974] "Is it legal to watch movies downloaded online with friends?"

[0975] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0976] Step 1:

[0977] The user enters a legal question in text format using the device's user interface and presses the "Submit" button. This obtains the legal question as input from the end user. An example of a specific prompt sentence is "Is it okay to watch a movie downloaded online with a friend?"

[0978] Step 2:

[0979] The device receives the text entered by the user and analyzes the user's emotions in real time using a facial recognition camera and a voice analysis microphone. The emotion analysis engine determines the user's emotional state from their facial expressions and tone of voice. The results of this analysis (e.g., the user is anxious) are used as input for the next step.

[0980] Step 3:

[0981] The device sends the user's question and the emotion analysis results to the server in the form of an HTTP request. The server receives this request and obtains the input text and emotion data. As a result, the server obtains the user's question and information about their emotional state as input.

[0982] Step 4:

[0983] The server analyzes the received question text using a natural language processing algorithm (e.g., SpaCy or NLTK). During this analysis, themes and keywords are extracted from the question. For example, keywords such as "online," "download," "movie," "watch with friends," and "okay" are extracted and used as input for the next step.

[0984] Step 5:

[0985] The server sends a query to a legal knowledge base (e.g., an SQL database) based on the extracted keywords, which searches for relevant legal information (e.g., copyright law, legal precedents, regulatory information, etc.) and obtains the information obtained from the query as output.

[0986] Step 6:

[0987] The server uses a generative AI model (e.g., GPT-3) to generate an answer based on the legal information it obtains. The answer is adjusted based on the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server might generate a gentle answer saying, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[0988] Step 7:

[0989] The server generates a response and sends it to the user's device. The device receives the response and displays it on the user's screen. This allows the user to obtain legal advice through their device. Links to relevant legal resources are also displayed, if necessary.

[0990] Step 8:

[0991] If a user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. For example, a link such as "Click here for more information" will be displayed, and the user can click it to begin the process of receiving professional assistance.

[0992] Step 9:

[0993] The server collects user feedback. User ratings and comments are collected and stored in a database. The server analyzes this feedback and updates the generative AI model to improve the accuracy of future answers. This process continuously improves the entire system.

[0994] (Application example 2)

[0995] 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."

[0996] For food delivery services, responding quickly and accurately to customer questions and complaints is crucial to maintaining customer satisfaction. However, previous systems struggled to generate personalized responses that took into account the user's emotional state. They also lacked the means to quickly provide appropriate legal information and expert assistance. This sometimes resulted in delayed responses to user complaints, leading to lower customer satisfaction.

[0997] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for the terminal to recognize the user's emotional state using facial recognition and voice analysis; means for the server to adjust the tone of the answer based on the recognized emotional state; and means for providing access to paid expert consultations when the user faces a serious legal problem. This enables personalized answers to be provided based on the user's emotional state and rapid provision of legal information and expert assistance.

[0998] A "means for users to enter legal questions" is a system that provides an interface, text box, and submit button for users to enter legal questions in text format using a terminal.

[0999] A "natural language processing algorithm" is a machine learning algorithm for understanding, analyzing, and processing human language, and is a technology used to extract keywords and intent from text data.

[1000] A "legal knowledge base" is a database that stores legal information and data, including copyright law, legal precedents, and regulatory information.

[1001] An "AI model" is an artificial intelligence model trained by machine learning algorithms and used to generate appropriate answers based on input data.

[1002] "Facial recognition" is a technology that uses image processing technology to detect a user's face and analyze their facial expressions and features.

[1003] "Voice analysis" is a technology that analyzes voice data and recognizes the user's tone of voice and emotions.

[1004] "Emotional state" refers to a psychological state inferred from a user's facial expression and tone of voice, and includes anxiety, relief, anger, etc.

[1005] "Access to Paid Expert Consultations" is a feature that provides links and procedures for users to receive expert legal assistance or consultations.

[1006] This invention provides a system for responding quickly and accurately to customer inquiries and complaints in a food delivery service. The system includes the following main components:

[1007] System program and processing explanation

[1008] Hardware and Software

[1009] 1. User Device

[1010] Users input questions using devices such as smartphones and tablets, which are equipped with cameras and include functions for facial recognition and voice analysis.

[1011] Technologies used: OpenCV (face recognition), TensorFlow (emotion recognition)

[1012] 2. Server

[1013] The server receives user questions, analyzes them, and generates answers, using spaCy for natural language processing and SQLite as the legal knowledge base.

[1014] Technologies used: Flask (web framework), spaCy (natural language processing), SQLite (database), machine learning model

[1015] Data processing and calculation

[1016] 1. Text input and question analysis

[1017] The user enters a legal question into the terminal and presses the submit button, which sends the entered question in text form to the server.

[1018] The server receives the question and performs text analysis using a natural language processing algorithm (spaCy) to extract key keywords.

[1019] 2. Obtaining legal information

[1020] Based on the extracted keywords, the server queries a legal knowledge base (SQLite) to retrieve relevant legal information, including regulations and laws related to food delivery services.

[1021] 3. Emotion recognition

[1022] The device uses a camera to capture a picture of the user's face in real time and sends the data to a server, which uses OpenCV and TensorFlow to recognize the user's emotional state.

[1023] 4. Answer generation and tone adjustment

[1024] The server uses an AI model to generate an appropriate response based on the legal information acquired and the user's emotional state, adjusting the tone of the response to be gentler if the emotional state is anxious.

[1025] 5. View Answers

[1026] The server generates a response and sends it to the user's device, which displays it to them and, if necessary, provides a link to access legal advice.

[1027] Examples and prompts

[1028] For example, if a user types a question like, "My order hasn't arrived yet, what should I do?" and looks anxious at the camera, the system will generate a response like this:

[1029] "We recommend you check to see if your order arrives soon. Don't worry, our support will be there shortly, just wait a moment."

[1030] In this way, the present invention provides personalized responses based on the user's emotional state, allowing for a fast and accurate response.

[1031] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1032] Step 1:

[1033] User question input

[1034] The user enters a legal question in text format using the device interface and presses the send button. At this time, the input text is stored in a variable called "question." The device also takes a real-time photo of the user's face with a camera and captures video frames for emotion recognition. The data sent is the question text and the video frames.

[1035] Step 2:

[1036] Sending and receiving questions

[1037] The device sends the question text and video frame as an HTTP request to the server. The server receives the request and stores the question text in the analysis variable "question text" and the video frame in the analysis variable "video frame."

[1038] Step 3:

[1039] Question analysis using natural language processing

[1040] The server analyzes the "question text" using a natural language processing algorithm (spaCy) to extract key keywords. The input is the "question text" and the output is the extracted keywords ("keywords"), which are used in subsequent database queries.

[1041] Step 4:

[1042] Submitting queries to the legal knowledge base

[1043] The server sends a query to a legal knowledge base (SQLite database) based on the extracted "keyword group" to retrieve related legal information. The input is the "keyword group" and the output is the related legal information "legal information." The information retrieved from the database includes precedents, regulations, and legal-related data.

[1044] Step 5:

[1045] emotion recognition

[1046] The server analyzes the received "video frames" using OpenCV and TensorFlow to recognize the user's emotional state. The input is the "video frame" and the output is the emotional state "emotional state." The emotional state is classified into categories such as "anxiety," "relief," and "anger."

[1047] Step 6:

[1048] Answer generation and tone control

[1049] The server uses an AI model to generate an appropriate answer based on the acquired "legal information" and "emotional state." If the emotional state is "anxious," it processes the answer by adjusting the tone to be gentler. The input is "legal information" and "emotional state," and the output is the final answer, "Answer."

[1050] Step 7:

[1051] Submitting and viewing answers

[1052] The server sends the generated "answer" to the user's device. The device displays the received answer to the user. If necessary, an access link to a legal expert is also added. The input is the "answer," and the output is the answer and link displayed on the user's screen.

[1053] If a user asks, "My order hasn't arrived yet, what should I do?" and looks anxious, the device will respond with, "We recommend that you check to see if your order is arriving soon. Don't worry, our support will be there shortly, so please wait a moment."

[1054] 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.

[1055] 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.

[1056] 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.

[1057] [Fourth embodiment]

[1058] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1059] 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.

[1060] 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).

[1061] 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.

[1062] 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.

[1063] 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).

[1064] 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.

[1065] 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.

[1066] 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.

[1067] 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.

[1068] 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.

[1069] 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.

[1070] 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."

[1071] The present invention is a system for enabling users to obtain quick and accurate answers to legal questions. The operation of this system will now be described in detail.

[1072] First, the user enters their legal question in text format into the terminal. The terminal provides a user interface with a text box for entering the question and a submit button. The user uses this input form to enter their question and then presses the submit button.

[1073] Next, the device sends the user's question to the server in the form of an HTTP request, which the server receives and retrieves the question text.

[1074] The server uses natural language processing algorithms to analyze the text based on the received question. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[1075] Based on these keywords, the server queries a legal knowledge base to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns the appropriate information for the query.

[1076] Based on the acquired information, the server uses an AI model to generate a response. This response contains specific content that is easy for the user to understand. For example, it can be output as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[1077] The generated answer is sent from the server to the device, which displays the answer on the user's screen, possibly with links to additional information or relevant legal resources, if necessary.

[1078] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, allowing the user to receive professional assistance.

[1079] Finally, the server collects user feedback and uses it to update the AI ​​model to improve the accuracy of future answers, a process that continuously improves the entire system.

[1080] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content, and is extremely beneficial to users as it allows them to quickly receive expert assistance for even serious legal issues.

[1081] The processing flow will be explained below.

[1082] Step 1:

[1083] An interface is displayed for the user to enter legal questions into the terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[1084] Step 2:

[1085] The device sends the user's question in text format to the server, which sends the question to the server as an HTTP request.

[1086] Step 3:

[1087] The server receives the HTTP request, retrieves the question text, and prepares it for analysis.

[1088] Step 4:

[1089] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[1090] Step 5:

[1091] The server sends a query to a legal knowledge base (database) based on the extracted keywords, where the query is an inquiry to search for relevant legal information.

[1092] Step 6:

[1093] The server retrieves relevant information from a legal knowledge base, which returns relevant legal information, precedents, and legal documents.

[1094] Step 7:

[1095] The server uses an AI model based on the information it acquires to generate specific answers for the user, which are designed to be easy for the user to understand.

[1096] Step 8:

[1097] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[1098] Step 9:

[1099] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[1100] Step 10:

[1101] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[1102] Step 11:

[1103] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[1104] Step 12:

[1105] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[1106] Example 1

[1107] 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."

[1108] There are challenges for users, such as the difficulty of getting fast and accurate answers to legal questions over the Internet, and the difficulty of quickly receiving paid legal assistance when users face serious legal issues. Furthermore, there is a need for the system to effectively utilize user feedback and be continuously improved.

[1109] 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.

[1110] In this invention, the server includes a means for receiving a user's question and analyzing it using a natural language processing algorithm, a means for sending a query to a legal knowledge base based on the extracted keywords to obtain information, and a means for generating an answer using a generative AI model based on the obtained information. This allows users to obtain quick and accurate legal answers, and enables them to quickly receive support from paid legal experts when facing serious legal issues. In addition, by collecting user feedback and updating the generative AI model, the accuracy of the next answer can be improved.

[1111] "User" means any person or entity that utilizes the System to enter legal questions and receive answers.

[1112] A "terminal" is an electronic device through which a user enters legal questions and displays responses from a server.

[1113] A "server" is a central computing device that receives a user's question, analyzes it, generates an answer, and sends it to the terminal.

[1114] A "natural language processing algorithm" is a technology that analyzes text entered by a user and extracts meaning and keywords.

[1115] "Keywords" are important words and phrases extracted from the question entered by the user to identify the meaning of the text.

[1116] A "legal knowledge base" is a database that stores legal information, including copyright law, legal precedents, and regulatory information.

[1117] A "generative AI model" is an artificial intelligence model that generates appropriate answers for users based on information obtained from a legal knowledge base.

[1118] An "answer" is a response message generated by the server in response to a user's question.

[1119] "Feedback" is the user's evaluation or opinion of the system's response.

[1120] A "paid legal consultation" is a paid legal advice service provided by a professional lawyer.

[1121] The present invention is a system for allowing a user to input a legal question and receive a prompt and appropriate answer based on the question, the system including a terminal, a server, and a legal knowledge base.

[1122] First, the user enters a legal question in text format into the device. The device provides a user interface, displaying a text box for entering the question and a submit button. For example, the user enters the question, "Is it legal to use music downloaded from YouTube for personal use?" and presses the submit button. At this time, the device detects the click event of the submit button, obtains the entered question text, and proceeds to the next step.

[1123] The device sends the user's question to the server in the form of an HTTP request. The HTTP request includes the question text. The device then generates an HTTP POST request including the question text and sends the data to the specified endpoint. This establishes network communication and the data reaches the server.

[1124] The server receives the HTTP request and retrieves the question text. It then uses natural language processing algorithms to analyze the text and extract the subject and keywords of the question. For example, if the server receives the question "Is it legal to download music from YouTube for personal use?", it uses a natural language processing library to extract the keywords "YouTube," "download," "personal use," and "legal."

[1125] The server sends a query to a legal knowledge base based on the extracted keywords to retrieve relevant legal information, for example, the server retrieves information about "copyright law" and "personal use" from the legal knowledge base.

[1126] Next, the server uses the generative AI model to generate a response based on the acquired legal information. For example, if the legal information returned is "personal use may be a copyright infringement," the generative AI model uses that information to generate a response such as "downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[1127] The generated answer is sent from the server to the device. The device displays the answer received from the server on the user's screen. If necessary, links to additional information or relevant legal resources are also displayed. For example, the device analyzes the received answer text and updates the user interface to display the text. A message is displayed on the screen stating, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[1128] Furthermore, if the user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. The user can click on this link to receive professional assistance. For example, the device may display a link on the screen that reads, "If you need more information, you can consult with a legal professional by clicking this link." and the user can click on it.

[1129] Finally, the server collects user feedback and uses it to update the generative AI model to improve the accuracy of future answers. For example, if a user rates the answer as "helpful," the server stores that feedback in a database and periodically uses it as training data for the generative AI model. This allows the entire system to continuously improve, improving the accuracy of future answers.

[1130] Prompt Sentence Examples

[1131] Here is an example prompt:

[1132] "Is it legal to download music from YouTube for personal use?"

[1133] "Is it illegal to post screenshots from a movie on a website?"

[1134] "Can I use free materials I find online for commercial purposes?"

[1135] In this way, users can minimize legal risks and safely use digital content. Furthermore, the entire system is continuously improved by updating the generative AI model based on feedback.

[1136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1137] Step 1:

[1138] Users enter and submit legal questions.

[1139] What it does: The device provides a text box and a submit button for the user to enter a question. The user enters a question such as "Is it legal to download music from YouTube for personal use?" and presses the submit button.

[1140] Input: Legal question text entered by the user

[1141] Output: Question text collected by the device

[1142] Step 2:

[1143] The device sends the user's question to the server.

[1144] Specific operation: The device generates an HTTP POST request containing the question text and sends it to the server. Network communication is established and the data arrives at the server.

[1145] Input: Question text collected by the device

[1146] Output: An HTTP request containing the question text arrives at the server.

[1147] Step 3:

[1148] The server receives and parses the question text.

[1149] What it does: The server receives an HTTP request, retrieves the question text, and uses a natural language processing algorithm to extract keywords such as "YouTube," "download," "personal," and "legal."

[1150] Input: HTTP request containing the question text

[1151] Output: Extracted keywords

[1152] Step 4:

[1153] The server queries the legal knowledge base to retrieve the information.

[1154] What happens: The server generates a database query using the keywords "copyright law" and "personal use" and performs a search against the legal knowledge base. Relevant legal information is retrieved from the database.

[1155] Input: Extracted keywords

[1156] Output: Information retrieved from the legal knowledge base

[1157] Step 5:

[1158] The server generates an answer using a generative AI model based on the information it obtains.

[1159] Specific operation: The server uses a generative AI model to generate an answer based on the legal information it has obtained. For example, it might generate an answer such as, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[1160] Input: Information retrieved from the legal knowledge base

[1161] Output: Answer text provided to the user

[1162] Step 6:

[1163] The server sends the generated response to the terminal.

[1164] Specific operation: The server generates an HTTP response containing the answer text and sends it to the device. The data reaches the device via the network.

[1165] Input: Answer text provided to the user

[1166] Output: HTTP response containing the answer text

[1167] Step 7:

[1168] The device displays the answer to the user.

[1169] What happens: The device parses the received response text and updates the user interface, displaying the response text on the screen and, if necessary, providing links to relevant legal resources.

[1170] Input: HTTP response containing the answer text

[1171] Output: The answer text and link that is displayed to the user

[1172] Step 8:

[1173] The device will display a link to access a paid legal consultation (if required).

[1174] What it does: The device displays a link on the screen that says, "For more information, you can contact a legal professional by following this link." The user can click it.

[1175] Input: Expert Consultation Link Needed

[1176] Output: A user-clickable consultation link

[1177] Step 9:

[1178] The server collects feedback and updates the generative AI model.

[1179] What it does: The server collects user feedback, stores it in a database, and periodically uses it as training data for the generative AI model, improving the accuracy of future answers.

[1180] Input: User feedback

[1181] Output: Updated generative AI model and improved answer accuracy

[1182] (Application example 1)

[1183] 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."

[1184] When users of autonomous vehicles encounter legal questions or problems, there is a lack of means to respond quickly and appropriately. In particular, there is a need for a system that can provide real-time answers to legal questions that arise while driving. To solve this problem, a system is needed that allows users to input questions through an intuitive user interface, including voice input, and quickly provides appropriate legal advice.

[1185] 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.

[1186] In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question and analyze the question using a natural language processing algorithm to extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for providing access to paid consultations with legal experts when the user faces a serious legal issue; means for inputting and transmitting the legal question via a user interface in the autonomous vehicle; means for inputting the legal question in voice form using the vehicle's voice input system; and means for providing an answer via the vehicle's touchscreen or voice output system, thereby enabling the user to receive prompt and appropriate legal advice while driving.

[1187] "User interface" means the means of input and output that a user uses to interact with a system, including touchscreens and voice input systems in autonomous vehicles.

[1188] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language, using a series of algorithms including text analysis and keyword extraction.

[1189] A "legal knowledge base" is a database that stores structured legal information, such as copyright law, case law, and regulatory information, and is intended to provide appropriate legal information in response to queries.

[1190] An "AI model" is a mathematical model that uses artificial intelligence technology to generate appropriate outputs for specific inputs, and is responsible for generating answers to legal questions.

[1191] A "voice input system" is a device or technology that allows a user to input instructions into a system through speech, and converts speech into text using speech recognition technology.

[1192] A "touch screen" is an input device that allows users to operate the device by touching the screen, allowing them to intuitively input questions and check answers.

[1193] A "legal advice system" is a set of computer systems that uses technologies such as natural language processing and AI models to provide appropriate advice on legal questions.

[1194] "Feedback" is information provided by users regarding their satisfaction with the system's responses and suggestions for improvement, and is used as data for improving the system.

[1195] "Consultation" means consultation to obtain expert advice on a specific issue, including conversations with paid legal professionals.

[1196] An "autonomous vehicle" is a vehicle that drives automatically using artificial intelligence and various sensors, and is equipped with technology that minimizes human intervention.

[1197] The system of the present invention is a legal advice system installed in an autonomous vehicle, and aims to provide users with prompt and appropriate answers to legal questions that arise while driving. This system operates by combining a user interface, natural language processing, a legal knowledge base, an AI model, and a voice input / output device.

[1198] System configuration

[1199] 1. User Interface:

[1200] It provides a means for users to input legal questions using touchscreens and voice input systems within autonomous vehicles.

[1201] 2. Voice input system:

[1202] It uses the SpeechRecognition library to recognize the user's speech and converts it to text using the Google Speech Recognition API. For example, if a user asks, "I didn't see that road sign just now. Does that mean I'm speeding?", the system will convert that speech to text.

[1203] 3. Data transmission:

[1204] Questions entered in text format via a voice input system or touchscreen are sent from the car's computer to the server in the form of an HTTP request.

[1205] 4. Text Analysis (Natural Language Processing):

[1206] The server analyzes the received question text using a natural language processing algorithm. As a result of the analysis, it extracts key keywords and themes. For example, in response to the question, "Is it legal to use music downloaded from YouTube for personal use?", the server extracts the keywords "YouTube," "download," "personal use," and "legal."

[1207] 5. Obtaining information from the legal knowledge base:

[1208] The server then queries a legal knowledge base based on the extracted keywords to retrieve relevant legal information, including copyright law, legal precedents, and regulatory information, and returns appropriate information for the query.

[1209] 6. Answer generation by AI model:

[1210] Based on the legal information obtained by the server, an AI model is used to generate a response in a user-friendly format. For example, the output would be something like, "Downloading music from YouTube for personal use may be a copyright infringement. We recommend obtaining permission from the copyright holder."

[1211] 7. Suggested answers:

[1212] The generated answers are then sent back into the vehicle and presented to the user via the touchscreen or via a voice output system, which uses the pyttsx3 library to play the text aloud.

[1213] 8. Additional options:

[1214] For serious legal issues, a link is also provided to allow for paid consultation with a legal expert using the vehicle's internet connection.

[1215] 9. Feedback collection and system learning:

[1216] The server collects user feedback and uses it as data to improve the accuracy of answers across the entire system, which will improve the accuracy of answers from the next time onwards.

[1217] Specific examples

[1218] As a concrete example, imagine a user asks the following question:

[1219] Question: "I didn't see the road sign just now. Does that count as speeding?"

[1220] Answer: "Even if you don't see the road signs, you still need to obey the speed limit. It may be a legal violation."

[1221] Prompt Sentence Examples

[1222] User question: "I didn't see the road sign just now, does that mean I'm speeding?"

[1223] Keywords: road signs, speeding

[1224] Search for relevant information in a legal knowledge base and generate the answer: "Even if you don't see the road sign, you must obey the speed limit. It may be a legal violation."

[1225] The system of this invention aims to provide quick and appropriate answers to legal questions while driving, allowing users to use self-driving vehicles with peace of mind.

[1226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1227] Step 1:

[1228] The user enters a legal question.

[1229] Specifically, a user inputs a question using a touchscreen or voice input system in an autonomous vehicle. When using a voice input system, the user verbally states the question, which the SpeechRecognition library converts into text. The input is the user's question, and the output is a text question.

[1230] Step 2:

[1231] The autonomous vehicle's terminal sends the question to the server.

[1232] Specifically, a text question is sent to the server in the form of an HTTP request. The input is the text question, and the output is an HTTP request to the server.

[1233] Step 3:

[1234] The server receives the question and analyzes it using natural language processing algorithms.

[1235] Specifically, the received text is parsed using natural language processing (NLP) algorithms (e.g., spaCy or NLTK libraries) to extract key keywords and intent, where the input is a textual question and the output is the extracted keywords and themes.

[1236] Step 4:

[1237] The server sends a query to a legal knowledge base based on the extracted keywords.

[1238] Specifically, the extracted keywords are used to query a legal knowledge base (database) to retrieve relevant legal information, where the input is the extracted keywords and the output is the legal information as a query result.

[1239] Step 5:

[1240] The server generates answers using an AI model based on the information it obtains.

[1241] Specifically, an AI model (such as GPT-4) is used to generate an answer based on the acquired legal information in a format that is easy for the user to understand. The input is information obtained from the legal knowledge base, and the output is the generated answer.

[1242] Step 6:

[1243] The server generates a response and sends it to the user's device.

[1244] Specifically, the generated answer is sent to the autonomous vehicle's terminal as an HTTP response. The input at this time is the generated answer, and the output is the HTTP response to the terminal.

[1245] Step 7:

[1246] The device displays the answer to the user.

[1247] Specifically, the answer is displayed on a touchscreen, or the answer is played aloud using a voice output system, which uses the pyttsx3 library to convert text to speech, where the input is the answer provided by the server, and the output is the information the user receives visually or audibly.

[1248] Step 8:

[1249] Providing paid legal consultations when users face serious legal issues.

[1250] Specifically, when a user requests additional advice, for example, a link to access a paid consultation is displayed on the touch screen, where the input is the user's request and the output is the link to access the consultation.

[1251] Step 9:

[1252] The server collects user feedback and updates the AI ​​model.

[1253] Specifically, it collects user-provided feedback, analyzes that data, adds it to the AI ​​model's training dataset, and retrains the model to improve answer accuracy in future iterations. The input is the user feedback, and the output is an updated AI model.

[1254] 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.

[1255] The present invention is a system that allows users to get fast and accurate answers to their legal questions. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the tone and content of the answers based on that information.

[1256] First, the user enters their legal question in text format into the terminal. At this time, the terminal displays a user interface, providing a text box for entering the question and a submit button. The user uses this interface to enter the question and presses the "Submit" button.

[1257] Next, the device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with features such as facial recognition and voice analysis, and these emotion engines are used to analyze the user's emotions in real time.

[1258] After the server receives the question, it uses natural language processing algorithms to analyze the text. As a result of the analysis, themes and keywords are extracted. For example, if a user asks, "Is it legal to use music downloaded from YouTube for personal use?", the server will extract the keywords "YouTube," "download," "personal use," and "legal."

[1259] Based on the extracted keywords, the server sends a query to a legal knowledge base (database) to retrieve relevant legal information. The legal knowledge base includes copyright law, legal precedents, regulatory information, etc., and returns appropriate information for the query.

[1260] Based on the information obtained, the server uses an AI model to generate a response. This response is adjusted taking into account the user's emotional state. For example, if the emotion engine detects that the user is anxious, the server will create a response in a gentler, more reassuring tone. For example, it might say, "Downloading music from YouTube for personal use may be a copyright infringement. If you are concerned, we recommend obtaining permission from the copyright holder."

[1261] The generated answer is sent from the server to the device, which displays the answer on the user's screen, along with links to additional information and relevant legal resources, if necessary.

[1262] Additionally, if a user faces a serious legal problem, the device will display a link to access a paid legal consultation, which will take the user through the process of obtaining professional assistance.

[1263] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[1264] The system of the present invention is designed to minimize legal risks and enable users to safely use digital content. It also takes into account the user's emotional state to provide more personalized and friendly answers. This is extremely beneficial for users, as they can quickly receive expert assistance even for serious legal issues.

[1265] The processing flow will be explained below.

[1266] Step 1:

[1267] The user operates an interface for entering legal questions into a terminal. A text box and a submit button are displayed, the user enters the question, and presses the "Submit" button.

[1268] Step 2:

[1269] The device asks the user questions and uses facial recognition and voice analysis to collect emotional data, analyzing the user's emotional state (e.g., anxiety, anger, excitement, etc.) from their facial expressions and voice tone.

[1270] Step 3:

[1271] The device sends the user's question text and emotion data to the server in the form of an HTTP request.

[1272] Step 4:

[1273] The server receives the HTTP request and retrieves the question text and emotion data.

[1274] Step 5:

[1275] The server uses natural language processing (NLP) algorithms to analyze the question text and extract topics and keywords, such as "YouTube," "download," "personal use," and "legal."

[1276] Step 6:

[1277] The server sends a query to a legal knowledge base (database) based on the extracted keywords to search for relevant legal information.

[1278] Step 7:

[1279] The server retrieves relevant information from a legal knowledge base, returning legal information, precedents, legal documents, etc.

[1280] Step 8:

[1281] The server uses an AI model to generate a response based on the information acquired and the user's emotional data. The tone and content of the response are adjusted according to the emotional data. For example, if the user is anxious, the response will be generated in a gentler tone.

[1282] Step 9:

[1283] The server generates an answer and sends it to the user's device. The answer is sent as an HTTP response.

[1284] Step 10:

[1285] The device receives the response from the server and displays the answer in a user interface, allowing the user to review the answer and get additional information if necessary.

[1286] Step 11:

[1287] If the user desires further legal advice or formal legal services, the device will display a link to access a paid legal consultation, which the user can click to proceed with obtaining professional assistance.

[1288] Step 12:

[1289] The server collects user feedback and updates the AI ​​model based on that feedback, which improves the accuracy of answers from the next time onwards.

[1290] Step 13:

[1291] The server continuously updates the legal knowledge base with the latest feedback and analytical data, improving the overall performance of the system, a process aimed at continuous improvement of the system.

[1292] Example 2

[1293] 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."

[1294] Previously, when users had legal questions, it was difficult to get a quick and accurate answer, and it was not possible to respond appropriately based on the user's emotional state. Furthermore, when users faced serious legal issues, it was difficult to receive appropriate support because there was no way to quickly access paid legal experts.

[1295] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for a terminal to analyze the user's emotions; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using a generative AI model based on the information obtained; means for the server to adjust the answer generated by the server based on the user's emotional state; means for the server to send the answer generated by the server to the user's terminal and for the terminal to display the answer to the user; and means for providing access to paid consultations with legal experts when the user faces a serious legal problem. This allows users to receive prompt and accurate legal advice and personalized responses according to their emotional state. It also allows users to receive prompt expert support even for serious legal issues.

[1296] "User" means any person who uses the System to enter legal questions and receive answers.

[1297] "Terminal" means the electronic device used by a User to enter legal questions and view answers.

[1298] "Emotion analysis" refers to the technology and process by which a device detects and analyzes a user's emotional state.

[1299] "Server" refers to the central processing system for processing legal inquiries received from Users, generating answers, and returning them to Users.

[1300] A "natural language processing algorithm" refers to an algorithm that analyzes text questions and extracts keywords and intent.

[1301] "Keywords" refer to important words or phrases extracted from a user's question.

[1302] A "legal knowledge base" refers to a database that stores legal information (e.g., laws, precedents, regulatory information, etc.).

[1303] "Query" refers to a search instruction sent by a server to a legal knowledge base.

[1304] "Generative AI model" refers to an artificial intelligence model that generates answers based on acquired legal information.

[1305] "Answer" refers to the response provided by the server to the user's question using a generative AI model.

[1306] "Feedback" refers to ratings and comments on system responses collected from users.

[1307] "Paid legal consultation" means legal consultation services provided for a fee.

[1308] "Access Link" means a connection that directs a user to a paid consultation with a legal professional.

[1309] "Tuning" refers to the process of changing the tone and content of the generated answers depending on the user's emotional state.

[1310] This invention is a system that allows users to quickly and accurately obtain answers to legal questions. Furthermore, it provides personalized responses by incorporating an emotion engine that recognizes the user's emotions and adjusts the tone and content of the response based on that information. To effectively implement this system, the following hardware and software are required:

[1311] First, the user enters their legal question in text format into the device. At this time, a user interface is displayed on the device, providing a text box for entering the question and a submit button. The user uses this interface to enter their question and presses the "Submit" button. An example of a question that a user might enter is, "Is it okay to watch a movie I downloaded online with my friends?"

[1312] The device sends the user's question in text format to the server. The question is sent in the form of an HTTP request, and the server receives the request and retrieves the question text. During this process, the device is equipped with a facial recognition camera and a voice analysis microphone, and these are used to analyze the user's emotions in real time using an emotion engine. Emotion analysis determines, for example, whether the user is feeling anxious based on their facial expressions and tone of voice when entering a question.

[1313] After the server receives the question, it performs text analysis using natural language processing algorithms (e.g., SpaCy or NLTK). This analysis extracts topics and keywords from the question. For example, if a user asks, "Is it okay to watch a movie I downloaded online with my friends?", the server extracts the keywords "online," "download," "movie," "watch with friends," and "okay."

[1314] Next, the server sends a query to a legal knowledge base (e.g., a database built with SQL) based on the extracted keywords to retrieve relevant legal information. The legal knowledge base stores copyright law, precedents, regulatory information, and other information, and returns appropriate information in response to the query. Based on the information retrieved by the server, a generative AI model (e.g., GPT-3) is used to generate an answer to the user's question.

[1315] The generated answer is adjusted to take into account the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server will create a gentler, more reassuring tone of response, such as, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[1316] The server then sends the generated answer to the device, which then displays it on the user's screen. The answer may also include links to additional information and related legal resources. Additionally, if the user faces a serious legal problem, the device may display a link to access a paid legal consultation. Clicking on this link will take the user through the process of obtaining professional assistance.

[1317] Finally, the server collects user feedback and updates the AI ​​model to improve the accuracy of answers in future queries, a process that continuously improves the entire system.

[1318] Examples of prompts:

[1319] "Is it legal to watch movies downloaded online with friends?"

[1320] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1321] Step 1:

[1322] The user enters a legal question in text format using the device's user interface and presses the "Submit" button. This obtains the legal question as input from the end user. An example of a specific prompt sentence is "Is it okay to watch a movie downloaded online with a friend?"

[1323] Step 2:

[1324] The device receives the text entered by the user and analyzes the user's emotions in real time using a facial recognition camera and a voice analysis microphone. The emotion analysis engine determines the user's emotional state from their facial expressions and tone of voice. The results of this analysis (e.g., the user is anxious) are used as input for the next step.

[1325] Step 3:

[1326] The device sends the user's question and the emotion analysis results to the server in the form of an HTTP request. The server receives this request and obtains the input text and emotion data. As a result, the server obtains the user's question and information about their emotional state as input.

[1327] Step 4:

[1328] The server analyzes the received question text using a natural language processing algorithm (e.g., SpaCy or NLTK). During this analysis, themes and keywords are extracted from the question. For example, keywords such as "online," "download," "movie," "watch with friends," and "okay" are extracted and used as input for the next step.

[1329] Step 5:

[1330] The server sends a query to a legal knowledge base (e.g., an SQL database) based on the extracted keywords, which searches for relevant legal information (e.g., copyright law, legal precedents, regulatory information, etc.) and obtains the information obtained from the query as output.

[1331] Step 6:

[1332] The server uses a generative AI model (e.g., GPT-3) to generate an answer based on the legal information it obtains. The answer is adjusted based on the user's emotional state. For example, if emotion analysis detects that the user is anxious, the server might generate a gentle answer saying, "Watching a movie downloaded online with friends may be a copyright infringement. If you are concerned, we recommend getting permission from the copyright holder."

[1333] Step 7:

[1334] The server generates a response and sends it to the user's device. The device receives the response and displays it on the user's screen. This allows the user to obtain legal advice through their device. Links to relevant legal resources are also displayed, if necessary.

[1335] Step 8:

[1336] If a user faces a serious legal problem, the device will display a link to access a paid consultation with a legal professional. For example, a link such as "Click here for more information" will be displayed, and the user can click it to begin the process of receiving professional assistance.

[1337] Step 9:

[1338] The server collects user feedback. User ratings and comments are collected and stored in a database. The server analyzes this feedback and updates the generative AI model to improve the accuracy of future answers. This process continuously improves the entire system.

[1339] (Application example 2)

[1340] 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."

[1341] For food delivery services, responding quickly and accurately to customer questions and complaints is crucial to maintaining customer satisfaction. However, previous systems struggled to generate personalized responses that took into account the user's emotional state. They also lacked the means to quickly provide appropriate legal information and expert assistance. This sometimes resulted in delayed responses to user complaints, leading to lower customer satisfaction.

[1342] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input a legal question; means for the server to receive the user's question, analyze the question using a natural language processing algorithm, and extract keywords and intent; means for the server to send a query to a legal knowledge base based on the extracted keywords and obtain relevant legal information; means for the server to generate an answer using an AI model based on the information obtained; means for the server to send the generated answer to the user's terminal and for the terminal to display the answer to the user; means for the terminal to recognize the user's emotional state using facial recognition and voice analysis; means for the server to adjust the tone of the answer based on the recognized emotional state; and means for providing access to paid expert consultations when the user faces a serious legal problem. This enables personalized answers to be provided based on the user's emotional state and rapid provision of legal information and expert assistance.

[1343] A "means for users to enter legal questions" is a system that provides an interface, text box, and submit button for users to enter legal questions in text format using a terminal.

[1344] A "natural language processing algorithm" is a machine learning algorithm for understanding, analyzing, and processing human language, and is a technology used to extract keywords and intent from text data.

[1345] A "legal knowledge base" is a database that stores legal information and data, including copyright law, legal precedents, and regulatory information.

[1346] An "AI model" is an artificial intelligence model trained by machine learning algorithms and used to generate appropriate answers based on input data.

[1347] "Facial recognition" is a technology that uses image processing technology to detect a user's face and analyze their facial expressions and features.

[1348] "Voice analysis" is a technology that analyzes voice data and recognizes the user's tone of voice and emotions.

[1349] "Emotional state" refers to a psychological state inferred from a user's facial expression and tone of voice, and includes anxiety, relief, anger, etc.

[1350] "Access to Paid Expert Consultations" is a feature that provides links and procedures for users to receive expert legal assistance or consultations.

[1351] This invention provides a system for responding quickly and accurately to customer inquiries and complaints in a food delivery service. The system includes the following main components:

[1352] System program and processing explanation

[1353] Hardware and Software

[1354] 1. User Device

[1355] Users input questions using devices such as smartphones and tablets, which are equipped with cameras and include functions for facial recognition and voice analysis.

[1356] Technologies used: OpenCV (face recognition), TensorFlow (emotion recognition)

[1357] 2. Server

[1358] The server receives user questions, analyzes them, and generates answers, using spaCy for natural language processing and SQLite as the legal knowledge base.

[1359] Technologies used: Flask (web framework), spaCy (natural language processing), SQLite (database), machine learning model

[1360] Data processing and calculation

[1361] 1. Text input and question analysis

[1362] The user enters a legal question into the terminal and presses the submit button, which sends the entered question in text form to the server.

[1363] The server receives the question and performs text analysis using a natural language processing algorithm (spaCy) to extract key keywords.

[1364] 2. Obtaining legal information

[1365] Based on the extracted keywords, the server queries a legal knowledge base (SQLite) to retrieve relevant legal information, including regulations and laws related to food delivery services.

[1366] 3. Emotion recognition

[1367] The device uses a camera to capture a picture of the user's face in real time and sends the data to a server, which uses OpenCV and TensorFlow to recognize the user's emotional state.

[1368] 4. Answer generation and tone adjustment

[1369] The server uses an AI model to generate an appropriate response based on the legal information acquired and the user's emotional state, adjusting the tone of the response to be gentler if the emotional state is anxious.

[1370] 5. View Answers

[1371] The server generates a response and sends it to the user's device, which displays it to them and, if necessary, provides a link to access legal advice.

[1372] Examples and prompts

[1373] For example, if a user types a question like, "My order hasn't arrived yet, what should I do?" and looks anxious at the camera, the system will generate a response like this:

[1374] "We recommend you check to see if your order arrives soon. Don't worry, our support will be there shortly, just wait a moment."

[1375] In this way, the present invention provides personalized responses based on the user's emotional state, allowing for a fast and accurate response.

[1376] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1377] Step 1:

[1378] User question input

[1379] The user enters a legal question in text format using the device interface and presses the send button. At this time, the input text is stored in a variable called "question." The device also takes a real-time photo of the user's face with a camera and captures video frames for emotion recognition. The data sent is the question text and the video frames.

[1380] Step 2:

[1381] Sending and receiving questions

[1382] The device sends the question text and video frame as an HTTP request to the server. The server receives the request and stores the question text in the analysis variable "question text" and the video frame in the analysis variable "video frame."

[1383] Step 3:

[1384] Question analysis using natural language processing

[1385] The server analyzes the "question text" using a natural language processing algorithm (spaCy) to extract key keywords. The input is the "question text" and the output is the extracted keywords ("keywords"), which are used in subsequent database queries.

[1386] Step 4:

[1387] Submitting queries to the legal knowledge base

[1388] The server sends a query to a legal knowledge base (SQLite database) based on the extracted "keyword group" to retrieve related legal information. The input is the "keyword group" and the output is the related legal information "legal information." The information retrieved from the database includes precedents, regulations, and legal-related data.

[1389] Step 5:

[1390] emotion recognition

[1391] The server analyzes the received "video frames" using OpenCV and TensorFlow to recognize the user's emotional state. The input is the "video frame" and the output is the emotional state "emotional state." The emotional state is classified into categories such as "anxiety," "relief," and "anger."

[1392] Step 6:

[1393] Answer generation and tone control

[1394] The server uses an AI model to generate an appropriate answer based on the acquired "legal information" and "emotional state." If the emotional state is "anxious," it processes the answer by adjusting the tone to be gentler. The input is "legal information" and "emotional state," and the output is the final answer, "Answer."

[1395] Step 7:

[1396] Submitting and viewing answers

[1397] The server sends the generated "answer" to the user's device. The device displays the received answer to the user. If necessary, an access link to a legal expert is also added. The input is the "answer," and the output is the answer and link displayed on the user's screen.

[1398] If a user asks, "My order hasn't arrived yet, what should I do?" and looks anxious, the device will respond with, "We recommend that you check to see if your order is arriving soon. Don't worry, our support will be there shortly, so please wait a moment."

[1399] 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.

[1400] 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.

[1401] 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.

[1402] 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.

[1403] 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.

[1404] 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.

[1405] 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).

[1406] 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.

[1407] 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."

[1408] 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.

[1409] 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).

[1410] 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.

[1411] 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.

[1412] 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.

[1413] 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.

[1414] 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.

[1415] 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.

[1416] 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.

[1417] 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.

[1418] 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.

[1419] 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.

[1420] The following is further disclosed regarding the above embodiment.

[1421] (Claim 1)

[1422] a means for users to enter legal questions;

[1423] A server receives a user's question, analyzes the question using a natural language processing algorithm, and extracts keywords and intent;

[1424] means for the server to query a legal knowledge base based on the extracted keywords to obtain relevant legal information;

[1425] A means for generating answers using an AI model based on the information acquired by the server;

[1426] means for transmitting the generated answer from the server to the user's terminal, and for the terminal to display the answer to the user;

[1427] and means for providing access to paid legal consultations when a user faces serious legal issues.

[1428] (Claim 2)

[1429] 10. The system of claim 1, further comprising means for the server to collect user feedback and analyze the feedback to update the AI ​​model to improve accuracy of subsequent answers.

[1430] (Claim 3)

[1431] 10. The system of claim 1, wherein the terminal further comprises means for displaying to the user an access link to a paid legal consultation and instructions for using the same.

[1432] "Example 1"

[1433] (Claim 1)

[1434] a means for users to enter legal questions;

[1435] a means for the terminal to provide a text box and a submit button for the user to enter a question;

[1436] a means by which the terminal transmits the user's question to the server;

[1437] A server receives a user's question, analyzes the question using a natural language processing algorithm, and extracts keywords and intent;

[1438] means for the server to query a legal knowledge base based on the extracted keywords to obtain relevant legal information;

[1439] A means for generating an answer using a generative AI model based on the information acquired by the server;

[1440] means for transmitting the generated answer from the server to the user's terminal, and for the terminal to display the answer to the user;

[1441] a means for providing a link by which the device can access a paid legal consultation;

[1442] A system including:

[1443] (Claim 2)

[1444] 10. The system of claim 1, further comprising means for the server to collect user feedback and analyze the feedback to update the generative AI model to improve accuracy of subsequent answers.

[1445] (Claim 3)

[1446] 10. The system of claim 1, wherein the terminal further comprises means for displaying to the user an access link to a paid legal consultation and instructions for using the same.

[1447] "Application Example 1"

[1448] (Claim 1)

[1449] a means for users to enter legal questions;

[1450] A server receives a user's question, analyzes the question using a natural language processing algorithm, and extracts keywords and intent;

[1451] means for the server to query a legal knowledge base based on the extracted keywords to obtain relevant legal information;

[1452] A means for generating answers using an AI model based on the information acquired by the server;

[1453] means for transmitting the generated answer from the server to the user's terminal, and for the terminal to display the answer to the user;

[1454] A means to provide users with access to paid legal consultations when they face serious legal issues;

[1455] a means for inputting and transmitting legal questions via a user interface within the autonomous vehicle;

[1456] means for inputting legal questions in voice form using a voice input system of the vehicle;

[1457] means for providing answers via a touch screen or voice output system in the vehicle;

[1458] A system including:

[1459] (Claim 2)

[1460] 10. The system of claim 1, further comprising means for the server to collect user feedback and analyze the feedback to update the AI ​​model to improve accuracy of subsequent answers.

[1461] (Claim 3)

[1462] 10. The system of claim 1, wherein the terminal further comprises means for displaying to the user an access link to a paid legal consultation and instructions for using the same.

[1463] "Example 2: Combining Emotion Engines"

[1464] (Claim 1)

[1465] a means for users to enter legal questions;

[1466] A means for the device to analyze the user's emotions;

[1467] A server receives a user's question, analyzes the question using a natural language processing algorithm, and extracts keywords and intent;

[1468] means for the server to query a legal knowledge base based on the extracted keywords to obtain relevant legal information;

[1469] A means for generating an answer using a generative AI model based on the information acquired by the server;

[1470] means for adjusting the server-generated response based on the user's emotional state;

[1471] means for transmitting the generated answer from the server to the user's terminal, and for the terminal to display the answer to the user;

[1472] A means to provide users with access to paid legal consultations when they face serious legal issues;

[1473] A system including:

[1474] (Claim 2)

[1475] 10. The system of claim 1, further comprising means for the server to collect user feedback and analyze the feedback to update the generative AI model to improve accuracy of subsequent answers.

[1476] (Claim 3)

[1477] 10. The system of claim 1, wherein the terminal further comprises means for displaying to the user an access link to a paid legal consultation and instructions for using the same.

[1478] "Application example 2 when combining emotion engines"

[1479] (Claim 1)

[1480] a means for users to enter legal questions;

[1481] A server receives a user's question, analyzes the question using a natural language processing algorithm, and extracts keywords and intent;

[1482] means for the server to query a legal knowledge base based on the extracted keywords to obtain relevant legal information;

[1483] A means for generating answers using an AI model based on the information acquired by the server;

[1484] means for transmitting the generated answer from the server to the user's terminal, and for the terminal to display the answer to the user;

[1485] A means for the device to recognize the user's emotional state using facial recognition and voice analysis;

[1486] means for the server to adjust the tone of the response based on the perceived emotional state;

[1487] A means to provide users with access to paid expert consultations when they face serious legal issues;

[1488] A system including:

[1489] (Claim 2)

[1490] 10. The system of claim 1, further comprising means for the server to collect user feedback and analyze the feedback to update the AI ​​model to improve accuracy of subsequent answers.

[1491] (Claim 3)

[1492] 10. The system of claim 1, wherein the terminal further comprises means for displaying to the user an access link to a paid expert consultation and instructions for using the same. [Explanation of symbols]

[1493] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for users to enter legal questions; A server receives a user's question, analyzes the question using a natural language processing algorithm, and extracts keywords and intent; means for the server to query a legal knowledge base based on the extracted keywords to obtain relevant legal information; A means for generating answers using an AI model based on the information acquired by the server; means for transmitting the generated answer from the server to the user's terminal, and for the terminal to display the answer to the user; and means for providing access to paid legal consultations when a user faces serious legal issues.

2. 10. The system of claim 1, further comprising means for the server to collect user feedback and analyze the feedback to update the AI ​​model to improve accuracy of subsequent answers.

3. 10. The system of claim 1, wherein the terminal further comprises means for displaying to the user an access link to a paid legal consultation and instructions for using the link.

Images