system

Abstract

We provide the system. [Solution] An input method for receiving user inquiries and analyzing their intent using natural language processing, A search means for searching a legal database based on the results analyzed by the input means and extracting relevant information, A generation means that generates a legal response based on the information extracted by the aforementioned search means, A system including a display means for presenting the answer created by the generation means to the user.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventional legal consultations have problems such as high costs and difficulty in quickly responding in situations where specialized knowledge is required. Also, when contacting a lawyer to receive a legal consultation, it is necessary to arrange an appointment, and in many cases, it is not possible to appropriately respond to urgent problems. There is a need to solve such problems and provide an efficient and convenient means for equally providing access to legal knowledge.

Means for Solving the Problems

[0005] This invention provides a system that offers prompt and accurate legal consultation by analyzing user inquiries using natural language processing and extracting necessary information from legal databases. Specifically, the system includes an input means for receiving and analyzing user input, a search means for searching for relevant information based on the analysis, a generation means for generating answers from the extracted information, and a display means for presenting the generated answers to the user. This system solves the time and cost problems associated with conventional legal consultations. Furthermore, by incorporating interaction means to enable additional questions and collaboration means for coordinating with experts, it enables more comprehensive legal support.

[0006] "User" refers to an individual or legal entity that uses this system to seek legal advice.

[0007] "Natural language processing" is a technology that uses computers to analyze human language and understand its meaning.

[0008] "Input method" refers to an interface for receiving and processing user inquiries.

[0009] "Search method" refers to a function for extracting relevant legal information from a database.

[0010] "Generative means" refers to the function of constructing appropriate answers from the retrieved information.

[0011] "Display means" refers to a method or device for presenting the generated answer to the user and aiding in their understanding.

[0012] An "interaction mechanism" is a method or function that allows a user to ask additional questions.

[0013] "Collaboration means" refers to a method or device for providing users with support from relevant experts. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention relates to a system that operates as a legal consultation agent, allowing users to input legal questions and receive quick and accurate answers. The system includes input means, search means, generation means, display means, interaction means, and linking means, and these functions efficiently support the user's legal consultation process.

[0036] The server is equipped with a natural language processing model that analyzes text input from users and interprets their intent. Users can input their questions via their terminal, for example, by entering specific questions such as, "Please tell me about divorce procedures." This input is sent to the server via the terminal's input method.

[0037] The server uses search mechanisms to access legal databases and retrieve legal information relevant to the user's question. This information is processed by generation mechanisms to construct an answer tailored to the user's needs. This answer is generated by translating legal jargon into the clearest possible language.

[0038] The terminal displays the answers received from the server to the user. This allows the user to immediately obtain specific advice regarding legal consultations. For example, they can understand the specific documents and legal procedures required for divorce proceedings.

[0039] Furthermore, if users wish to ask additional questions based on the answers provided, they can engage in further dialogue using the interaction tools. Additionally, if specialized legal interpretations are required, the system offers the option to connect with experts in that field using the collaboration tools.

[0040] In this way, this system provides rapid access to legal knowledge and lowers the barrier to seeking legal advice, thereby helping users resolve their legal problems.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users enter specific legal questions through the user interface on their device. For example, they might enter text such as, "Please tell me about the legal procedures regarding inheritance."

[0044] Step 2:

[0045] The terminal prepares the data received from the user into the necessary format for transmission to the server and then transfers it to the server.

[0046] Step 3:

[0047] The server inputs the received text data into a natural language processing model to analyze the intent behind the user's question. This analysis extracts keywords and themes related to the relevant legal domain.

[0048] Step 4:

[0049] The server uses search methods to search legal databases based on extracted keywords and collects relevant legal information and case precedents.

[0050] Step 5:

[0051] The server uses collected legal information and generation tools to construct answers to user questions. During this process, it simplifies terminology and employs techniques to ensure clarity as needed.

[0052] Step 6:

[0053] The server sends the generated response to the terminal. It formats the data into the necessary format for display on the user's terminal.

[0054] Step 7:

[0055] The device displays the received responses to the user. These responses may include a feature to highlight important information.

[0056] Step 8:

[0057] Based on the displayed answers, users can ask additional questions about any further concerns. In this case, they can initiate further discussions using interaction tools.

[0058] Step 9:

[0059] If necessary, users can choose to consult with experts through various means of collaboration. This includes the ability to send connection requests to relevant experts.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] In legal consultations, there is a need to provide users with an environment where they can obtain information quickly and accurately. Furthermore, a system is needed that allows users to acquire legal information in an easily understandable format and to easily connect with experts as needed. Traditional legal consultations are time-consuming and expensive, and access is limited, posing challenges to efficient information acquisition and consultation.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes acquisition means for acquiring information from the user and interpreting its intent through natural language processing, query means for querying an information database and extracting relevant information, and assembly means for assembling the information. This allows the user to efficiently acquire legal information, make additional inquiries, and easily collaborate with experts.

[0065] A "user" is someone who uses the system to obtain legal information.

[0066] "Acquisition method" refers to the means of obtaining information from users and incorporating that information into the system.

[0067] "Natural language processing" is a technology that enables computers to understand and process text data written in languages ​​that humans normally use.

[0068] "Interpreting intent" means understanding the meaning of user questions and requests contained in text data and accurately grasping their content.

[0069] A "search method" is a means of searching a database, finding information related to the entered keywords or themes, and retrieving it.

[0070] An "information database" is a collection of information that systematically stores data related to the law.

[0071] "Assembly methods" refer to means of constructing information and answers in a clear and easy-to-understand format for the user, based on the information acquired.

[0072] "Presentation method" refers to a means of showing assembled information or answers to the user.

[0073] A "dialogue mechanism" is a mechanism that allows users to ask more detailed questions or request additional information.

[0074] "Connection means" refers to methods that enable direct communication between users and experts.

[0075] This invention provides a system that delivers legal information quickly and accurately, creating an environment where users can easily seek legal advice. The system is primarily composed of a server and terminals, enabling users to obtain legal information.

[0076] The user enters legal questions through the terminal. For example, the user might enter the question, "Please tell me about divorce procedures," using the terminal's input device. The terminal converts this input into a signal and sends it to the server.

[0077] The server receives the input information and interprets the user's intent using natural language processing techniques. This process employs generative AI models, specifically natural language processing models such as GPT and BERT. This allows the server to accurately understand the question and prepare an appropriate response.

[0078] Based on the interpreted intent, the server queries the information database and retrieves relevant information. This information is stored in a legal database and includes important information and procedural details for the user.

[0079] The acquired information is organized using the server's assembly method and structured in a way that is easy for the user to understand. Even information that frequently uses legal terminology is rephrased and organized in a way that is easy for the user to understand.

[0080] Finally, the server sends this configured information back to the terminal, which then displays it visually to the user. This allows the user to immediately see specific advice and procedural steps regarding legal consultations.

[0081] Furthermore, if a user has additional questions, they can enter them again through the terminal, and the server can repeat the process of receiving these questions and providing new information. For example, if a user enters a prompt such as "Please tell me how to calculate inheritance tax," detailed information will be provided accordingly.

[0082] This system allows users to efficiently obtain legal information and easily connect with experts when advanced consultations are needed.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] The user enters legal questions through the terminal. Specifically, the user uses a keyboard or voice input device to enter questions such as, "Please tell me about divorce procedures," and this information is captured by the terminal's input system. The entered data is prepared as formatted text for processing in the next step.

[0086] Step 2:

[0087] The terminal sends the entered question to the server. The data is transmitted over the network, and in this process, the input data is converted into data packets. Specifically, a signal is sent to the server using an internet connection. The server receives this signal and prepares for the next step.

[0088] Step 3:

[0089] The server analyzes the received text data using a natural language processing model. A generative AI model is then used to interpret the intent behind the text. For example, the server uses a GPT model to extract context and keywords to understand the meaning of the user's question. This generates analysis results, which are then converted into a data format for further processing.

[0090] Step 4:

[0091] The server searches the information database based on the analysis results. The server generates database queries and retrieves relevant legal information. Specifically, it extracts data on necessary documents and procedural steps related to "divorce proceedings." During this process, the information is filtered and prioritized.

[0092] Step 5:

[0093] The server assembly method involves structuring the extracted information in a way that is easily understood by the user. Legal terminology is replaced with easily understandable general terms, and explanatory text is constructed. The generated text is prepared in a user-friendly format and converted into a displayable format in the next step.

[0094] Step 6:

[0095] The server sends the generated response to the terminal. The terminal renders the received information on the screen and presents it to the user. The terminal displays the response as easy-to-read text or graphical output, making it ready for immediate use.

[0096] Step 7:

[0097] If the user has further questions, they can use the terminal to make additional inquiries. The terminal will then accept user interaction again and prepare to send a new prompt to the server. This allows the server to start a new processing cycle and answer questions repeatedly.

[0098] (Application Example 1)

[0099] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] There is a challenge in providing users with timely and accurate legal information when they need legal advice. Furthermore, even when specialized expertise is required, there is a need for methods that users can easily access. Under these circumstances, there is a demand for providing means that users can easily seek legal advice even within the home.

[0101] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0102] In this invention, the server includes an input means that receives voice input from a user and analyzes its intent using natural language processing; a search means that searches a storage device containing legal information based on the results analyzed by the input means and extracts relevant information; and a generation means that generates a legal response based on the information extracted by the search means and presents it to the user in a form that includes voice output. This enables users to have legal consultations via voice within their homes, obtain information immediately, and use it to solve problems.

[0103] A "user" is an individual who uses this system to seek legal advice.

[0104] "Voice input" is a method of capturing a user's speech as digital data via a microphone or computer terminal.

[0105] "Natural language processing" is a technology that interprets the language spoken naturally by humans and converts it into a format that can be processed by computers.

[0106] A "storage device" is a device that stores legal data and information and makes it accessible as needed.

[0107] A "search function" is a function that searches for data within a storage device according to specified conditions and extracts relevant information.

[0108] "Generation method" refers to the technology that constructs answers to be provided to the user based on the extracted information.

[0109] A "voice output device" is a device that allows the user to hear the generated response, and it uses speech synthesis technology to produce the voice.

[0110] A "display device" is a device used to visually present the generated response to the user.

[0111] Embodiments of the present invention will now be described. Users can consult with legal experts via voice through a consumer robot. This robot is equipped with a voice input means, a natural language processing unit, a legal information storage device, a voice output device, and a display device.

[0112] First, when a user asks a legal question to the robot by voice, the voice input device captures this voice as text data. This input is then interpreted by a natural language processing unit. The natural language processing unit uses a generative AI model to analyze the intent of the user's question.

[0113] Based on the analyzed intent, the server searches the legal information storage device and extracts relevant legal information. This information is then assembled into a user-friendly format through a generation mechanism.

[0114] The compiled legal information is provided to the user verbally via an audio output device. Additionally, detailed information is displayed on a display screen as needed, providing a visual representation to the user.

[0115] For example, if a user asks the robot, "Please tell me about the divorce process," the robot will convert the question from speech to text and search legal databases. It can then find the most relevant information about the divorce process and necessary documents and explain it to the user via voice and display. This entire process is automated and fast.

[0116] An example of a prompt message is, "Please provide legal information regarding divorce proceedings." Through such prompts, the system can provide accurate legal information that meets the user's needs.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The user inputs legal questions into the robot via voice. This voice input is captured by the device through the microphone and converted into text data using speech recognition technology. This text data becomes the input for the next process.

[0120] Step 2:

[0121] The device uses a generative AI model to analyze the intent of text converted from speech. This analysis uses natural language processing techniques to identify the context and key keywords in the text data and extract legal themes. The output of this step is the legal topic inferred based on the user's question.

[0122] Step 3:

[0123] Based on the output of step 2, the server searches the legal information storage device. An efficient search algorithm is used to extract relevant information from the database regarding the specified legal topic. The legal information is the output of this step.

[0124] Step 4:

[0125] The server uses a generative AI model to generate legal answers tailored to the user, based on the acquired legal information. This generation process involves replacing legal jargon with simpler language, creating text that is easily understandable to the user. The output of this step is the detailed legal advice that has been generated.

[0126] Step 5:

[0127] The terminal outputs the legal advice generated in step 4 to the user via an audio output device. It also visually displays the legal advice on a display device. This provides the user with information through both audio and visual means. The output consists of the audioized legal consultation results and the text displayed on the screen.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention provides a system for realizing a legal consultation agent that combines an emotion engine that recognizes the user's emotions. This system can provide more personalized legal consultations by receiving consultations from users and analyzing their emotions.

[0130] The server incorporates an emotion engine, which not only uses a natural language processing model to analyze the intent behind user input but also uses the emotion engine to identify the user's emotional state. Based on the text data of user input, this system recognizes emotions such as positive, negative, and neutral. For example, if the input is "I am very confused by this situation," the system will analyze the emotion of confusion.

[0131] After an emotion is recognized, the server uses that emotion information to search for appropriate legal databases through a search mechanism, and then uses a generation mechanism to construct an emotion-sensitive response based on the information obtained. This system can adjust the tone and style of the response according to the emotion. For example, if the user is feeling anxious or worried, the response will use more reassuring language.

[0132] Furthermore, the device includes a function that visually displays the generated answers to the user and highlights important information. By viewing these answers, users can obtain specific and practical legal advice tailored to their specific situation.

[0133] Furthermore, based on the user's emotional state identified by the emotion engine, it also includes a function that suggests direct collaboration with experts as needed. For example, for users exhibiting particularly strong anxiety or distress, it can provide the opportunity to receive direct professional support by offering options for consulting with appropriate experts.

[0134] By utilizing this system, legal counseling agents can not only provide legal information but also deliver legal support in a more humane and easily understandable way that is tailored to the user's emotions. In this way, the present invention improves the user's legal counseling experience and provides a new form of legal consultation.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] Users enter their inquiries through an input interface on their device. For example, they might enter text such as, "I'm feeling anxious about a recent problem at work and would like to know about legal solutions."

[0138] Step 2:

[0139] The terminal converts user input into an appropriate format and sends it to the server. This input data includes the user's direct needs.

[0140] Step 3:

[0141] The server passes the received input data to a natural language processing engine to analyze the text content. Simultaneously, it uses an emotion engine to identify emotions (e.g., anxiety) contained in the user's text.

[0142] Step 4:

[0143] The server uses search mechanisms to retrieve appropriate information from legal databases, reflecting the user's emotional state. By performing emotion-based filtering, it selects more relevant information.

[0144] Step 5:

[0145] The server uses generation tools to construct appropriate responses based on the search results. At this stage, it considers the emotions identified by the emotion engine and adjusts the tone and expression of the response. For example, it might use phrasing that alleviates anxiety.

[0146] Step 6:

[0147] The server sends the assembled response to the terminal. The response is written in polite language tailored to the user.

[0148] Step 7:

[0149] The device visually displays the received responses to the user. This display highlights important information and is designed to be easy for the user to understand.

[0150] Step 8:

[0151] Based on the displayed answers, users can request further explanations or enter new questions. Additional dialogue is possible through interactive means.

[0152] Step 9:

[0153] If the emotion engine identifies a strong emotional response, the server will suggest direct contact with an expert to the user. This suggestion will be made through the contact mechanism if additional expert assistance is needed.

[0154] (Example 2)

[0155] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0156] Traditional legal consultation systems often provide general legal information without considering the user's specific feelings, failing to adequately address the emotional issues they face. As a result, users often lack the necessary information and struggle to reach satisfactory solutions. Furthermore, a lack of proper coordination with experts hindered the provision of prompt and effective support.

[0157] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0158] In this invention, the server includes an input means for receiving user information and determining its intentions and emotions, a search means for searching a data set while considering emotions, and a generation means for generating an emotionally sensitive response. This enables humane legal consultations that are tailored to the user's emotions.

[0159] A "user" refers to an individual or legal entity that uses the system to seek legal advice.

[0160] "Natural language analysis" refers to the technology of understanding the intent and emotions of human speech from text data, and utilizes natural language processing techniques.

[0161] "Input means" refers to an interface or method for receiving text information from a user.

[0162] A "data set" refers to a database or storage device that contains legal information.

[0163] "Search means" refers to a method or apparatus for searching a data set based on specific conditions and extracting relevant information.

[0164] "Generative means" refers to a method or apparatus for creating a response based on extracted information and user sentiment.

[0165] "Display means" refers to a method or device for visually presenting the generated response to the user.

[0166] "Expert collaboration means" refers to methods or devices for connecting users with appropriate experts as needed.

[0167] A "generative AI model" refers to a model that uses artificial intelligence to generate responses that are tailored to the user's emotions.

[0168] A "prompt statement" refers to an input statement used to obtain a specified output from a generative AI model.

[0169] This invention is a legal consultation agent system that takes user emotions into consideration and includes three main components: a server, a terminal, and a user, for performing specific processing.

[0170] The server receives text input of legal consultations from users and has the capability to perform natural language processing on it. This processing uses Python's NLTK and Transformers natural language processing libraries. By identifying the user's intent and emotions from the analysis results, the emotion engine labels the user's emotional state. For example, if a user inputs "I am very confused about this situation," the server labels it with the emotion "confused." This emotion information is used for effective searching within the data set.

[0171] Subsequently, the server extracts legal information based on the user's emotional state from the data set through a search mechanism. For example, SQL or NoSQL technologies are used for the database and information storage. Based on the retrieved information, the server uses a generative AI model to generate a legal response tailored to the user. OpenAI's GPT-3® is used as the generative AI model, and the tone of the response is adjusted according to the user's emotions through prompts. Prompts are instructions that control the output of the generative AI model, and are in the form of, "The user has the following input: 'I am confused about the boundary with my neighbor.' Please provide legally appropriate advice in this situation while also providing reassurance."

[0172] The input data received from the user is smoothly transmitted to the server using a secure communication protocol, and the generated response is visually displayed to the user on the device. This process utilizes the interface within the device, and important information is highlighted using CSS styles. As a result, users can receive specific, practical legal advice that resonates with their emotions.

[0173] Furthermore, the server includes a feature that suggests connecting users with experts, especially those exhibiting strong anxiety or confusion. This connection is facilitated by using APIs that connect to external platforms, presenting users with access links to experts. This is a crucial element in ensuring users can quickly obtain the additional support they need.

[0174] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0175] Step 1:

[0176] The user enters their legal consultation details via a terminal. The user's input is sent to the terminal in text format and then transmitted to the server via a secure protocol. This input process initiates the system's analysis of the user's legal questions and consultation details.

[0177] Step 2:

[0178] The server receives input text from the user and passes it to a natural language processing model to determine intent and emotion. A natural language processing library is used for data analysis; specifically, the input text is tokenized, the context is analyzed, and the emotional state is labeled. The output is data indicating the user's emotional state, such as "confused" or "anxious."

[0179] Step 3:

[0180] Based on the analyzed emotional state, the server searches legal databases and extracts information relevant to the user's situation. The input here is the emotional data obtained in the previous step, and the database search uses queries utilizing SQL or NoSQL. The output is legal information related to the user's intentions and emotions.

[0181] Step 4:

[0182] The server uses a generative AI model to generate user-oriented responses based on search results. Here, legal information and sentiment data are taken as input, and prompts are used to instruct the generative AI model, which then generates responses with adjusted tone. The prompts act as queues for generating sentiment-sensitive responses, resulting in emotionally considerate legal advice responses as output.

[0183] Step 5:

[0184] The terminal visually displays the generated response received from the server to the user. This display uses CSS styles to highlight important parts, making it easy for the user to understand and review all the legal advice. This allows the user to quickly obtain specific and practical legal advice.

[0185] Step 6:

[0186] The server provides options for connecting with a professional if a specific emotional state, particularly anxiety or confusion, is detected. This step involves executing an API that takes the user's emotional data as input to prepare a connection to a professional consultation platform. The output presents access links and booking options for professionals relevant to the user.

[0187] (Application Example 2)

[0188] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0189] Current legal consultation systems often provide information without considering the user's feelings, resulting in inadequate support for users' situations. In particular, when users seek advice on legally important but emotionally complex matters, a response that considers their feelings is needed, rather than simply providing information. Furthermore, smooth coordination with experts tailored to the user's emotional state is required.

[0190] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0191] In this invention, the server includes an input means for receiving consultation content from a user and analyzing its intent and emotions using natural language processing; a search means for searching for legal information sources and extracting relevant information based on the results analyzed by the input means; and a generation means for generating a legal response that takes emotions into consideration based on the information extracted by the search means. This makes it possible to provide legal consultation that is sensitive to the user's emotions.

[0192] An "input method" is an interface that receives information such as voice or text from the user and processes it in a digital format.

[0193] "Natural language processing" is a technology that enables computers to understand, analyze, and generate responses to human language.

[0194] "Emotion analysis" is a technology that identifies emotions from information provided by the user and represents that state using numerical values ​​or text.

[0195] A "search tool" is a function that references a specified information source and quickly and accurately extracts the necessary relevant information.

[0196] "Generation method" refers to the process of constructing a response to the user based on extracted information and analysis results.

[0197] "Display means" refers to devices or technologies used to present results to the user visually or audibly.

[0198] A "collaboration method" refers to a system that proposes connections with suitable experts and other relevant parties, and facilitates the rapid sharing of necessary information.

[0199] A "computational means" is a calculation function that analyzes input data and derives appropriate results.

[0200] This invention relates to a system for providing legal consultations that take into consideration the user's feelings. The system is accessible to the user through various devices and is implemented in the following manner.

[0201] The server uses advanced speech recognition technology and the Google® Speech-to-Text API to convert the user's speech into text data. The converted text data is then analyzed using natural language processing techniques. In this process, OpenAI's large-scale language model is used to identify the user's intent and related legal matters.

[0202] Next, sentiment analysis is performed using the analyzed data. This is done using IBM Watson® Tone Analyzer, which classifies the user's emotional state as positive, negative, or neutral. Based on this sentiment information, the server appropriately adjusts the tone and style of the legal advice.

[0203] The search system incorporates a mechanism that references legal information sources, allowing for the rapid extraction of important information. The generated answers are displayed via terminals such as robots. These terminals are equipped with displays, allowing users to visually confirm the answers.

[0204] In a real-world example, if a user asks, "I'm worried that my working conditions might be in violation of the law," the system will provide information on relevant labor laws and offer appropriate advice in a friendly and helpful manner. In this way, users can receive legal support tailored to their specific situation.

[0205] Furthermore, if the user's emotional state is very negative, the server will suggest options for connecting with appropriate professionals. This gives the user the opportunity to receive professional support as needed.

[0206] An example of a prompt message would be, "When a user is seeking legal advice that includes emotions, generate advice appropriate to their emotional state and suggest referral to a specialist if necessary." This invention will enable more humane and understandable legal support.

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The user provides voice input to the device. The device uses a high-performance microphone to send the information to the server as voice data.

[0210] Step 2:

[0211] The server converts the received audio data into text data using the Google Speech-to-Text API. In this process, the audio signal is converted into digital text information. The output text data is then passed on to the next step.

[0212] Step 3:

[0213] The server uses OpenAI's large-scale language model to analyze the intent behind the text data. This analysis clarifies the legal content of the consultation. The user's intent and related legal items obtained from the analysis are then sent to the next processing step.

[0214] Step 4:

[0215] The server uses IBM Watson Tone Analyzer to analyze emotions from text data. In this step, the data is output as an emotional state (positive, negative, neutral). This emotional information is then used in the next step of generating responses.

[0216] Step 5:

[0217] The server searches for legal information sources based on the analyzed intent and sentiment information. It extracts relevant legal information and provides it for the next step. The search results include relevant legal articles and past case precedents.

[0218] Step 6:

[0219] Based on the information extracted in the previous step, the server generates legal advice that takes the user's emotions into consideration. It utilizes a generative AI model to construct the response with an appropriate tone and phrasing. This response is then formatted for display output.

[0220] Step 7:

[0221] The device presents the user with a formatted response sent from the server. The display visually shows the information and, in some cases, provides audio output. The user sees the response and receives reassuring support based on sensitive information.

[0222] Step 8:

[0223] If the server determines that the user's emotional state is negative and further support is needed, it will suggest an option to consult with a relevant expert. This option connects the user with a suitable expert and allows them to receive direct assistance.

[0224] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0225] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0226] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0230] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0231] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0232] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0233] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0234] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0235] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0236] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0237] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0238] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0239] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0240] This invention relates to a system that operates as a legal consultation agent, allowing users to input legal questions and receive quick and accurate answers. The system includes input means, search means, generation means, display means, interaction means, and linking means, and these functions efficiently support the user's legal consultation process.

[0241] The server is equipped with a natural language processing model that analyzes text input from users and interprets their intent. Users can input their questions via their terminal, for example, by entering specific questions such as, "Please tell me about divorce procedures." This input is sent to the server via the terminal's input method.

[0242] The server uses search mechanisms to access legal databases and retrieve legal information relevant to the user's question. This information is processed by generation mechanisms to construct an answer tailored to the user's needs. This answer is generated by translating legal jargon into the clearest possible language.

[0243] The terminal displays the answers received from the server to the user. This allows the user to immediately obtain specific advice regarding legal consultations. For example, they can understand the specific documents and legal procedures required for divorce proceedings.

[0244] Furthermore, if users wish to ask additional questions based on the answers provided, they can engage in further dialogue using the interaction tools. Additionally, if specialized legal interpretations are required, the system offers the option to connect with experts in that field using the collaboration tools.

[0245] In this way, this system provides rapid access to legal knowledge and lowers the barrier to seeking legal advice, thereby helping users resolve their legal problems.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] Users enter specific legal questions through the user interface on their device. For example, they might enter text such as, "Please tell me about the legal procedures regarding inheritance."

[0249] Step 2:

[0250] The terminal prepares the data received from the user into the necessary format for transmission to the server and then transfers it to the server.

[0251] Step 3:

[0252] The server inputs the received text data into a natural language processing model to analyze the intent behind the user's question. This analysis extracts keywords and themes related to the relevant legal domain.

[0253] Step 4:

[0254] The server uses search methods to search legal databases based on extracted keywords and collects relevant legal information and case precedents.

[0255] Step 5:

[0256] The server uses collected legal information and generation tools to construct answers to user questions. During this process, it simplifies terminology and employs techniques to ensure clarity as needed.

[0257] Step 6:

[0258] The server sends the generated response to the terminal. It formats the data into the necessary format for display on the user's terminal.

[0259] Step 7:

[0260] The device displays the received responses to the user. These responses may include a feature to highlight important information.

[0261] Step 8:

[0262] Based on the displayed answers, users can ask additional questions about any further concerns. In this case, they can initiate further discussions using interaction tools.

[0263] Step 9:

[0264] If necessary, users can choose to consult with experts through various means of collaboration. This includes the ability to send connection requests to relevant experts.

[0265] (Example 1)

[0266] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0267] In legal consultations, there is a need to provide users with an environment where they can obtain information quickly and accurately. Furthermore, a system is needed that allows users to acquire legal information in an easily understandable format and to easily connect with experts as needed. Traditional legal consultations are time-consuming and expensive, and access is limited, posing challenges to efficient information acquisition and consultation.

[0268] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0269] In this invention, the server includes acquisition means for acquiring information from the user and interpreting its intent through natural language processing, query means for querying an information database and extracting relevant information, and assembly means for assembling the information. This allows the user to efficiently acquire legal information, make additional inquiries, and easily collaborate with experts.

[0270] A "user" is someone who uses the system to obtain legal information.

[0271] "Acquisition method" refers to the means of obtaining information from users and incorporating that information into the system.

[0272] "Natural language processing" is a technology that enables computers to understand and process text data written in languages ​​that humans normally use.

[0273] "Interpreting intent" means understanding the meaning of user questions and requests contained in text data and accurately grasping their content.

[0274] A "search method" is a means of searching a database, finding information related to the entered keywords or themes, and retrieving it.

[0275] An "information database" is a collection of information that systematically stores data related to the law.

[0276] "Assembly methods" refer to means of constructing information and answers in a clear and easy-to-understand format for the user, based on the information acquired.

[0277] "Presentation method" refers to a means of showing assembled information or answers to the user.

[0278] A "dialogue mechanism" is a mechanism that allows users to ask more detailed questions or request additional information.

[0279] "Connection means" refers to methods that enable direct communication between users and experts.

[0280] This invention provides a system that delivers legal information quickly and accurately, creating an environment where users can easily seek legal advice. The system is primarily composed of a server and terminals, enabling users to obtain legal information.

[0281] The user enters legal questions through the terminal. For example, the user might enter the question, "Please tell me about divorce procedures," using the terminal's input device. The terminal converts this input into a signal and sends it to the server.

[0282] The server receives the input information and interprets the user's intention by making full use of natural language processing technology. In this process, a generative AI model is used, specifically, a natural language processing model such as GPT or BERT is employed. As a result, the server accurately understands the content of the question and prepares an appropriate answer.

[0283] Based on the interpreted intention, the server queries the information database and retrieves relevant information. This information is stored in a legal-related database and includes important information for the user and details of procedures.

[0284] The retrieved information is sorted by the server's assembly means and configured in a form suitable for the user's understanding. Information with frequent use of legal terms is also sorted in a paraphrased form that is easy for the user to understand.

[0285] Finally, the server sends back this configured information to the terminal, and the terminal visually displays it to the user. As a result, the user can immediately check specific advice and procedure steps regarding legal consultations.

[0286] Furthermore, if the user wants to ask additional questions, they can input the questions again through the terminal, and the server can repeat the process of receiving it and providing new information. As a specific example, when a prompt sentence such as "Please teach me the calculation method of inheritance tax" is input, detailed information corresponding to it is provided.

[0287] With this system, users can efficiently obtain legal information and can easily connect to experts when high-level consultations are required.

[0288] The flow of specific processing in Example 1 will be described using FIG. 11.

[0289] Step 1:

[0290] The user enters legal questions through the terminal. Specifically, the user uses a keyboard or voice input device to enter questions such as, "Please tell me about divorce procedures," and this information is captured by the terminal's input system. The entered data is prepared as formatted text for processing in the next step.

[0291] Step 2:

[0292] The terminal sends the entered question to the server. The data is transmitted over the network, and in this process, the input data is converted into data packets. Specifically, a signal is sent to the server using an internet connection. The server receives this signal and prepares for the next step.

[0293] Step 3:

[0294] The server analyzes the received text data using a natural language processing model. A generative AI model is then used to interpret the intent behind the text. For example, the server uses a GPT model to extract context and keywords to understand the meaning of the user's question. This generates analysis results, which are then converted into a data format for further processing.

[0295] Step 4:

[0296] The server searches the information database based on the analysis results. The server generates database queries and retrieves relevant legal information. Specifically, it extracts data on necessary documents and procedural steps related to "divorce proceedings." During this process, the information is filtered and prioritized.

[0297] Step 5:

[0298] The server assembly method involves structuring the extracted information in a way that is easily understood by the user. Legal terminology is replaced with easily understandable general terms, and explanatory text is constructed. The generated text is prepared in a user-friendly format and converted into a displayable format in the next step.

[0299] Step 6:

[0300] The server sends the generated response to the terminal. The terminal renders the received information on the screen and presents it to the user. The terminal displays the response as easy-to-read text or graphical output, making it ready for immediate use.

[0301] Step 7:

[0302] If the user has further questions, they can use the terminal to make additional inquiries. The terminal will then accept user interaction again and prepare to send a new prompt to the server. This allows the server to start a new processing cycle and answer questions repeatedly.

[0303] (Application Example 1)

[0304] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0305] There is a challenge in providing users with timely and accurate legal information when they need legal advice. Furthermore, even when specialized expertise is required, there is a need for methods that users can easily access. Under these circumstances, there is a demand for providing means that users can easily seek legal advice even within the home.

[0306] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0307] In this invention, the server includes an input means for receiving voice input from a user and analyzing its intention through natural language processing, a search means for searching a storage device containing legal-related information based on the result analyzed by the input means and extracting relevant information, and a generation means for generating a legal answer based on the information extracted by the search means and presenting it to the user in a form including voice output. Thereby, the user can conduct legal consultations via voice within the home, obtain information immediately, and lead to problem-solving.

[0308] A "user" is an individual who uses this system to conduct legal consultations.

[0309] "Voice input" is a means for capturing a user's speech as digital data via a microphone or computer terminal.

[0310] "Natural language processing" is a technology for interpreting the words that humans speak naturally and converting them into a form that can be processed by a computer.

[0311] A "storage device" is a device that accumulates legal-related data and information and enables access as needed.

[0312] "Search means" is a function for searching data in a storage device according to specified conditions and extracting relevant information.

[0313] "Generation means" is a technology for assembling an answer to be provided to the user based on the extracted information.

[0314] A "voice output device" is a device for letting the user hear the generated answer and emits voice using voice synthesis technology.

[0315] A "display device" is a device for visually presenting the generated answer to the user.

[0316] Embodiments of the present invention will now be described. Users can consult with legal experts via voice through a consumer robot. This robot is equipped with a voice input means, a natural language processing unit, a legal information storage device, a voice output device, and a display device.

[0317] First, when a user asks a legal question to the robot by voice, the voice input device captures this voice as text data. This input is then interpreted by a natural language processing unit. The natural language processing unit uses a generative AI model to analyze the intent of the user's question.

[0318] Based on the analyzed intent, the server searches the legal information storage device and extracts relevant legal information. This information is then assembled into a user-friendly format through a generation mechanism.

[0319] The compiled legal information is provided to the user verbally via an audio output device. Additionally, detailed information is displayed on a display screen as needed, providing a visual representation to the user.

[0320] For example, if a user asks the robot, "Please tell me about the divorce process," the robot will convert the question from speech to text and search legal databases. It can then find the most relevant information about the divorce process and necessary documents and explain it to the user via voice and display. This entire process is automated and fast.

[0321] An example of a prompt message is, "Please provide legal information regarding divorce proceedings." Through such prompts, the system can provide accurate legal information that meets the user's needs.

[0322] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0323] Step 1:

[0324] The user inputs legal questions into the robot via voice. This voice input is captured by the device through the microphone and converted into text data using speech recognition technology. This text data becomes the input for the next process.

[0325] Step 2:

[0326] The device uses a generative AI model to analyze the intent of text converted from speech. This analysis uses natural language processing techniques to identify the context and key keywords in the text data and extract legal themes. The output of this step is the legal topic inferred based on the user's question.

[0327] Step 3:

[0328] Based on the output of step 2, the server searches the legal information storage device. An efficient search algorithm is used to extract relevant information from the database regarding the specified legal topic. The legal information is the output of this step.

[0329] Step 4:

[0330] The server uses a generative AI model to generate legal answers tailored to the user, based on the acquired legal information. This generation process involves replacing legal jargon with simpler language, creating text that is easily understandable to the user. The output of this step is the detailed legal advice that has been generated.

[0331] Step 5:

[0332] The terminal outputs the legal advice generated in step 4 to the user via an audio output device. It also visually displays the legal advice on a display device. This provides the user with information through both audio and visual means. The output consists of the audioized legal consultation results and the text displayed on the screen.

[0333] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0334] This invention provides a system for realizing a legal consultation agent that combines an emotion engine that recognizes the user's emotions. This system can provide more personalized legal consultations by receiving consultations from users and analyzing their emotions.

[0335] The server incorporates an emotion engine, which not only uses a natural language processing model to analyze the intent behind user input but also uses the emotion engine to identify the user's emotional state. Based on the text data of user input, this system recognizes emotions such as positive, negative, and neutral. For example, if the input is "I am very confused by this situation," the system will analyze the emotion of confusion.

[0336] After an emotion is recognized, the server uses that emotion information to search for appropriate legal databases through a search mechanism, and then uses a generation mechanism to construct an emotion-sensitive response based on the information obtained. This system can adjust the tone and style of the response according to the emotion. For example, if the user is feeling anxious or worried, the response will use more reassuring language.

[0337] Furthermore, the device includes a function that visually displays the generated answers to the user and highlights important information. By viewing these answers, users can obtain specific and practical legal advice tailored to their specific situation.

[0338] Furthermore, based on the user's emotional state identified by the emotion engine, it also includes a function that suggests direct collaboration with experts as needed. For example, for users exhibiting particularly strong anxiety or distress, it can provide the opportunity to receive direct professional support by offering options for consulting with appropriate experts.

[0339] By utilizing this system, legal counseling agents can not only provide legal information but also deliver legal support in a more humane and easily understandable way that is tailored to the user's emotions. In this way, the present invention improves the user's legal counseling experience and provides a new form of legal consultation.

[0340] The following describes the processing flow.

[0341] Step 1:

[0342] Users enter their inquiries through an input interface on their device. For example, they might enter text such as, "I'm feeling anxious about a recent problem at work and would like to know about legal solutions."

[0343] Step 2:

[0344] The terminal converts user input into an appropriate format and sends it to the server. This input data includes the user's direct needs.

[0345] Step 3:

[0346] The server passes the received input data to a natural language processing engine to analyze the text content. Simultaneously, it uses an emotion engine to identify emotions (e.g., anxiety) contained in the user's text.

[0347] Step 4:

[0348] The server uses search mechanisms to retrieve appropriate information from legal databases, reflecting the user's emotional state. By performing emotion-based filtering, it selects more relevant information.

[0349] Step 5:

[0350] The server uses generation tools to construct appropriate responses based on the search results. At this stage, it considers the emotions identified by the emotion engine and adjusts the tone and expression of the response. For example, it might use phrasing that alleviates anxiety.

[0351] Step 6:

[0352] The server sends the assembled response to the terminal. The response is written in polite language tailored to the user.

[0353] Step 7:

[0354] The device visually displays the received responses to the user. This display highlights important information and is designed to be easy for the user to understand.

[0355] Step 8:

[0356] Based on the displayed answers, users can request further explanations or enter new questions. Additional dialogue is possible through interactive means.

[0357] Step 9:

[0358] If the emotion engine identifies a strong emotional response, the server will suggest direct contact with an expert to the user. This suggestion will be made through the contact mechanism if additional expert assistance is needed.

[0359] (Example 2)

[0360] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0361] Traditional legal consultation systems often provide general legal information without considering the user's specific feelings, failing to adequately address the emotional issues they face. As a result, users often lack the necessary information and struggle to reach satisfactory solutions. Furthermore, a lack of proper coordination with experts hindered the provision of prompt and effective support.

[0362] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0363] In this invention, the server includes an input means for receiving user information and determining its intentions and emotions, a search means for searching a data set while considering emotions, and a generation means for generating an emotionally sensitive response. This enables humane legal consultations that are tailored to the user's emotions.

[0364] A "user" refers to an individual or legal entity that uses the system to seek legal advice.

[0365] "Natural language analysis" refers to the technology of understanding the intent and emotions of human speech from text data, and utilizes natural language processing techniques.

[0366] "Input means" refers to an interface or method for receiving text information from a user.

[0367] A "data set" refers to a database or storage device that contains legal information.

[0368] "Search means" refers to a method or apparatus for searching a data set based on specific conditions and extracting relevant information.

[0369] "Generative means" refers to a method or apparatus for creating a response based on extracted information and user sentiment.

[0370] "Display means" refers to a method or device for visually presenting the generated response to the user.

[0371] "Expert collaboration means" refers to methods or devices for connecting users with appropriate experts as needed.

[0372] A "generative AI model" refers to a model that uses artificial intelligence to generate responses that are tailored to the user's emotions.

[0373] A "prompt statement" refers to an input statement used to obtain a specified output from a generative AI model.

[0374] This invention is a legal consultation agent system that takes user emotions into consideration and includes three main components: a server, a terminal, and a user, for performing specific processing.

[0375] The server receives text input of legal consultations from users and has the capability to perform natural language processing on it. This processing uses Python's NLTK and Transformers natural language processing libraries. By identifying the user's intent and emotions from the analysis results, the emotion engine labels the user's emotional state. For example, if a user inputs "I am very confused about this situation," the server labels it with the emotion "confused." This emotion information is used for effective searching within the data set.

[0376] Subsequently, the server extracts legal information based on the user's emotional state from the data set through search mechanisms. For example, SQL or NoSQL technologies are used for the database and information storage. Based on the retrieved information, the server uses a generative AI model to generate a legal response tailored to the user. OpenAI's GPT-3 is used as the generative AI model, and the tone of the response is adjusted according to the user's emotions through prompts. Prompts are instructions that control the output of the generative AI model, and are in the form of, "The user has the following input: 'I am confused about the boundary with my neighbor.' Please provide legally appropriate advice in this situation while also providing reassurance."

[0377] The input data received from the user is smoothly transmitted to the server using a secure communication protocol, and the generated response is visually displayed to the user on the device. This process utilizes the interface within the device, and important information is highlighted using CSS styles. As a result, users can receive specific, practical legal advice that resonates with their emotions.

[0378] Furthermore, the server includes a feature that suggests connecting users with experts, especially those exhibiting strong anxiety or confusion. This connection is facilitated by using APIs that connect to external platforms, presenting users with access links to experts. This is a crucial element in ensuring users can quickly obtain the additional support they need.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] The user enters their legal consultation details via a terminal. The user's input is sent to the terminal in text format and then transmitted to the server via a secure protocol. This input process initiates the system's analysis of the user's legal questions and consultation details.

[0382] Step 2:

[0383] The server receives input text from the user and passes it to a natural language processing model to determine intent and emotion. A natural language processing library is used for data analysis; specifically, the input text is tokenized, the context is analyzed, and the emotional state is labeled. The output is data indicating the user's emotional state, such as "confused" or "anxious."

[0384] Step 3:

[0385] Based on the analyzed emotional state, the server searches legal databases and extracts information relevant to the user's situation. The input here is the emotional data obtained in the previous step, and the database search uses queries utilizing SQL or NoSQL. The output is legal information related to the user's intentions and emotions.

[0386] Step 4:

[0387] The server uses a generative AI model to generate user-oriented responses based on search results. Here, legal information and sentiment data are taken as input, and prompts are used to instruct the generative AI model, which then generates responses with adjusted tone. The prompts act as queues for generating sentiment-sensitive responses, resulting in emotionally considerate legal advice responses as output.

[0388] Step 5:

[0389] The terminal visually displays the generated response received from the server to the user. This display uses CSS styles to highlight important parts, making it easy for the user to understand and review all the legal advice. This allows the user to quickly obtain specific and practical legal advice.

[0390] Step 6:

[0391] The server provides options for connecting with a professional if a specific emotional state, particularly anxiety or confusion, is detected. This step involves executing an API that takes the user's emotional data as input to prepare a connection to a professional consultation platform. The output presents access links and booking options for professionals relevant to the user.

[0392] (Application Example 2)

[0393] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0394] Current legal consultation systems often provide information without considering the user's feelings, resulting in inadequate support for users' situations. In particular, when users seek advice on legally important but emotionally complex matters, a response that considers their feelings is needed, rather than simply providing information. Furthermore, smooth coordination with experts tailored to the user's emotional state is required.

[0395] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0396] In this invention, the server includes an input means for receiving consultation content from a user and analyzing its intent and emotions using natural language processing; a search means for searching for legal information sources and extracting relevant information based on the results analyzed by the input means; and a generation means for generating a legal response that takes emotions into consideration based on the information extracted by the search means. This makes it possible to provide legal consultation that is sensitive to the user's emotions.

[0397] An "input method" is an interface that receives information such as voice or text from the user and processes it in a digital format.

[0398] "Natural language processing" is a technology that enables computers to understand, analyze, and generate responses to human language.

[0399] "Emotion analysis" is a technology that identifies emotions from information provided by the user and represents that state using numerical values ​​or text.

[0400] A "search tool" is a function that references a specified information source and quickly and accurately extracts the necessary relevant information.

[0401] "Generation method" refers to the process of constructing a response to the user based on extracted information and analysis results.

[0402] "Display means" refers to devices or technologies used to present results to the user visually or audibly.

[0403] A "collaboration method" refers to a system that proposes connections with suitable experts and other relevant parties, and facilitates the rapid sharing of necessary information.

[0404] A "computational means" is a calculation function that analyzes input data and derives appropriate results.

[0405] This invention relates to a system for providing legal consultations that take into consideration the user's feelings. The system is accessible to the user through various devices and is implemented in the following manner.

[0406] The server uses advanced speech recognition technology and the Google Speech-to-Text API to convert the user's speech into text data. The converted text data is then analyzed using natural language processing techniques. In this process, OpenAI's large-scale language model is used to identify the user's intent and related legal matters.

[0407] Next, sentiment analysis is performed using the analyzed data. This is done using IBM Watson Tone Analyzer, which classifies the user's emotional state as positive, negative, or neutral. Based on this sentiment information, the server appropriately adjusts the tone and style of the legal advice.

[0408] The search system incorporates a mechanism that references legal information sources, allowing for the rapid extraction of important information. The generated answers are displayed via terminals such as robots. These terminals are equipped with displays, allowing users to visually confirm the answers.

[0409] In a real-world example, if a user asks, "I'm worried that my working conditions might be in violation of the law," the system will provide information on relevant labor laws and offer appropriate advice in a friendly and helpful manner. In this way, users can receive legal support tailored to their specific situation.

[0410] Furthermore, if the user's emotional state is very negative, the server will suggest options for connecting with appropriate professionals. This gives the user the opportunity to receive professional support as needed.

[0411] An example of a prompt message would be, "When a user is seeking legal advice that includes emotions, generate advice appropriate to their emotional state and suggest referral to a specialist if necessary." This invention will enable more humane and understandable legal support.

[0412] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0413] Step 1:

[0414] The user provides voice input to the device. The device uses a high-performance microphone to send the information to the server as voice data.

[0415] Step 2:

[0416] The server converts the received audio data into text data using the Google Speech-to-Text API. In this process, the audio signal is converted into digital text information. The output text data is then passed on to the next step.

[0417] Step 3:

[0418] The server uses OpenAI's large-scale language model to analyze the intent behind the text data. This analysis clarifies the legal content of the consultation. The user's intent and related legal items obtained from the analysis are then sent to the next processing step.

[0419] Step 4:

[0420] The server uses IBM Watson Tone Analyzer to analyze emotions from text data. In this step, the data is output as an emotional state (positive, negative, neutral). This emotional information is then used in the next step of generating responses.

[0421] Step 5:

[0422] The server searches for legal information sources based on the analyzed intent and sentiment information. It extracts relevant legal information and provides it for the next step. The search results include relevant legal articles and past case precedents.

[0423] Step 6:

[0424] Based on the information extracted in the previous step, the server generates legal advice that takes the user's emotions into consideration. It utilizes a generative AI model to construct the response with an appropriate tone and phrasing. This response is then formatted for display output.

[0425] Step 7:

[0426] The device presents the user with a formatted response sent from the server. The display visually shows the information and, in some cases, provides audio output. The user sees the response and receives reassuring support based on sensitive information.

[0427] Step 8:

[0428] If the server determines that the user's emotional state is negative and further support is needed, it will suggest an option to consult with a relevant expert. This option connects the user with a suitable expert and allows them to receive direct assistance.

[0429] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0430] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0431] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0432] [Third Embodiment]

[0433] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0434] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0435] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0436] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0437] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0438] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0439] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0440] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0441] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0442] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0443] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0444] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0445] This invention relates to a system that operates as a legal consultation agent, allowing users to input legal questions and receive quick and accurate answers. The system includes input means, search means, generation means, display means, interaction means, and linking means, and these functions efficiently support the user's legal consultation process.

[0446] The server is equipped with a natural language processing model that analyzes text input from users and interprets their intent. Users can input their questions via their terminal, for example, by entering specific questions such as, "Please tell me about divorce procedures." This input is sent to the server via the terminal's input method.

[0447] The server uses search mechanisms to access legal databases and retrieve legal information relevant to the user's question. This information is processed by generation mechanisms to construct an answer tailored to the user's needs. This answer is generated by translating legal jargon into the clearest possible language.

[0448] The terminal displays the answers received from the server to the user. This allows the user to immediately obtain specific advice regarding legal consultations. For example, they can understand the specific documents and legal procedures required for divorce proceedings.

[0449] Furthermore, if users wish to ask additional questions based on the answers provided, they can engage in further dialogue using the interaction tools. Additionally, if specialized legal interpretations are required, the system offers the option to connect with experts in that field using the collaboration tools.

[0450] In this way, this system provides rapid access to legal knowledge and lowers the barrier to seeking legal advice, thereby helping users resolve their legal problems.

[0451] The following describes the processing flow.

[0452] Step 1:

[0453] Users enter specific legal questions through the user interface on their device. For example, they might enter text such as, "Please tell me about the legal procedures regarding inheritance."

[0454] Step 2:

[0455] The terminal prepares the data received from the user into the necessary format for transmission to the server and then transfers it to the server.

[0456] Step 3:

[0457] The server inputs the received text data into a natural language processing model to analyze the intent behind the user's question. This analysis extracts keywords and themes related to the relevant legal domain.

[0458] Step 4:

[0459] The server uses search methods to search legal databases based on extracted keywords and collects relevant legal information and case precedents.

[0460] Step 5:

[0461] The server uses collected legal information and generation tools to construct answers to user questions. During this process, it simplifies terminology and employs techniques to ensure clarity as needed.

[0462] Step 6:

[0463] The server sends the generated response to the terminal. It formats the data into the necessary format for display on the user's terminal.

[0464] Step 7:

[0465] The device displays the received responses to the user. These responses may include a feature to highlight important information.

[0466] Step 8:

[0467] Based on the displayed answers, users can ask additional questions about any further concerns. In this case, they can initiate further discussions using interaction tools.

[0468] Step 9:

[0469] If necessary, users can choose to consult with experts through various means of collaboration. This includes the ability to send connection requests to relevant experts.

[0470] (Example 1)

[0471] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0472] In legal consultations, there is a need to provide users with an environment where they can obtain information quickly and accurately. Furthermore, a system is needed that allows users to acquire legal information in an easily understandable format and to easily connect with experts as needed. Traditional legal consultations are time-consuming and expensive, and access is limited, posing challenges to efficient information acquisition and consultation.

[0473] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0474] In this invention, the server includes acquisition means for acquiring information from the user and interpreting its intent through natural language processing, query means for querying an information database and extracting relevant information, and assembly means for assembling the information. This allows the user to efficiently acquire legal information, make additional inquiries, and easily collaborate with experts.

[0475] A "user" is someone who uses the system to obtain legal information.

[0476] "Acquisition method" refers to the means of obtaining information from users and incorporating that information into the system.

[0477] "Natural language processing" is a technology that enables computers to understand and process text data written in languages ​​that humans normally use.

[0478] "Interpreting intent" means understanding the meaning of user questions and requests contained in text data and accurately grasping their content.

[0479] A "search method" is a means of searching a database, finding information related to the entered keywords or themes, and retrieving it.

[0480] An "information database" is a collection of information that systematically stores data related to the law.

[0481] "Assembly methods" refer to means of constructing information and answers in a clear and easy-to-understand format for the user, based on the information acquired.

[0482] "Presentation method" refers to a means of showing assembled information or answers to the user.

[0483] A "dialogue mechanism" is a mechanism that allows users to ask more detailed questions or request additional information.

[0484] "Connection means" refers to methods that enable direct communication between users and experts.

[0485] This invention provides a system that delivers legal information quickly and accurately, creating an environment where users can easily seek legal advice. The system is primarily composed of a server and terminals, enabling users to obtain legal information.

[0486] The user enters legal questions through the terminal. For example, the user might enter the question, "Please tell me about divorce procedures," using the terminal's input device. The terminal converts this input into a signal and sends it to the server.

[0487] The server receives the input information and interprets the user's intent using natural language processing techniques. This process employs generative AI models, specifically natural language processing models such as GPT and BERT. This allows the server to accurately understand the question and prepare an appropriate response.

[0488] Based on the interpreted intent, the server queries the information database and retrieves relevant information. This information is stored in a legal database and includes important information and procedural details for the user.

[0489] The acquired information is organized using the server's assembly method and structured in a way that is easy for the user to understand. Even information that frequently uses legal terminology is rephrased and organized in a way that is easy for the user to understand.

[0490] Finally, the server sends this configured information back to the terminal, which then displays it visually to the user. This allows the user to immediately see specific advice and procedural steps regarding legal consultations.

[0491] Furthermore, if a user has additional questions, they can enter them again through the terminal, and the server can repeat the process of receiving these questions and providing new information. For example, if a user enters a prompt such as "Please tell me how to calculate inheritance tax," detailed information will be provided accordingly.

[0492] This system allows users to efficiently obtain legal information and easily connect with experts when advanced consultations are needed.

[0493] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0494] Step 1:

[0495] The user enters legal questions through the terminal. Specifically, the user uses a keyboard or voice input device to enter questions such as, "Please tell me about divorce procedures," and this information is captured by the terminal's input system. The entered data is prepared as formatted text for processing in the next step.

[0496] Step 2:

[0497] The terminal sends the entered question to the server. The data is transmitted over the network, and in this process, the input data is converted into data packets. Specifically, a signal is sent to the server using an internet connection. The server receives this signal and prepares for the next step.

[0498] Step 3:

[0499] The server analyzes the received text data using a natural language processing model. A generative AI model is then used to interpret the intent behind the text. For example, the server uses a GPT model to extract context and keywords to understand the meaning of the user's question. This generates analysis results, which are then converted into a data format for further processing.

[0500] Step 4:

[0501] The server searches the information database based on the analysis results. The server generates database queries and retrieves relevant legal information. Specifically, it extracts data on necessary documents and procedural steps related to "divorce proceedings." During this process, the information is filtered and prioritized.

[0502] Step 5:

[0503] The server assembly method involves structuring the extracted information in a way that is easily understood by the user. Legal terminology is replaced with easily understandable general terms, and explanatory text is constructed. The generated text is prepared in a user-friendly format and converted into a displayable format in the next step.

[0504] Step 6:

[0505] The server sends the generated response to the terminal. The terminal renders the received information on the screen and presents it to the user. The terminal displays the response as easy-to-read text or graphical output, making it ready for immediate use.

[0506] Step 7:

[0507] If the user has further questions, they can use the terminal to make additional inquiries. The terminal will then accept user interaction again and prepare to send a new prompt to the server. This allows the server to start a new processing cycle and answer questions repeatedly.

[0508] (Application Example 1)

[0509] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0510] There is a challenge in providing users with timely and accurate legal information when they need legal advice. Furthermore, even when specialized expertise is required, there is a need for methods that users can easily access. Under these circumstances, there is a demand for providing means that users can easily seek legal advice even within the home.

[0511] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0512] In this invention, the server includes an input means that receives voice input from a user and analyzes its intent using natural language processing; a search means that searches a storage device containing legal information based on the results analyzed by the input means and extracts relevant information; and a generation means that generates a legal response based on the information extracted by the search means and presents it to the user in a form that includes voice output. This enables users to have legal consultations via voice within their homes, obtain information immediately, and use it to solve problems.

[0513] A "user" is an individual who uses this system to seek legal advice.

[0514] "Voice input" is a method of capturing a user's speech as digital data via a microphone or computer terminal.

[0515] "Natural language processing" is a technology that interprets the language spoken naturally by humans and converts it into a format that can be processed by computers.

[0516] A "storage device" is a device that stores legal data and information and makes it accessible as needed.

[0517] A "search function" is a function that searches for data within a storage device according to specified conditions and extracts relevant information.

[0518] "Generation method" refers to the technology that constructs answers to be provided to the user based on the extracted information.

[0519] A "voice output device" is a device that allows the user to hear the generated response, and it uses speech synthesis technology to produce the voice.

[0520] A "display device" is a device used to visually present the generated response to the user.

[0521] Embodiments of the present invention will now be described. Users can consult with legal experts via voice through a consumer robot. This robot is equipped with a voice input means, a natural language processing unit, a legal information storage device, a voice output device, and a display device.

[0522] First, when a user asks a legal question to the robot by voice, the voice input device captures this voice as text data. This input is then interpreted by a natural language processing unit. The natural language processing unit uses a generative AI model to analyze the intent of the user's question.

[0523] Based on the analyzed intent, the server searches the legal information storage device and extracts relevant legal information. This information is then assembled into a user-friendly format through a generation mechanism.

[0524] The compiled legal information is provided to the user verbally via an audio output device. Additionally, detailed information is displayed on a display screen as needed, providing a visual representation to the user.

[0525] For example, if a user asks the robot, "Please tell me about the divorce process," the robot will convert the question from speech to text and search legal databases. It can then find the most relevant information about the divorce process and necessary documents and explain it to the user via voice and display. This entire process is automated and fast.

[0526] An example of a prompt message is, "Please provide legal information regarding divorce proceedings." Through such prompts, the system can provide accurate legal information that meets the user's needs.

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] The user inputs legal questions into the robot via voice. This voice input is captured by the device through the microphone and converted into text data using speech recognition technology. This text data becomes the input for the next process.

[0530] Step 2:

[0531] The device uses a generative AI model to analyze the intent of text converted from speech. This analysis uses natural language processing techniques to identify the context and key keywords in the text data and extract legal themes. The output of this step is the legal topic inferred based on the user's question.

[0532] Step 3:

[0533] Based on the output of step 2, the server searches the legal information storage device. An efficient search algorithm is used to extract relevant information from the database regarding the specified legal topic. The legal information is the output of this step.

[0534] Step 4:

[0535] The server uses a generative AI model to generate legal answers tailored to the user, based on the acquired legal information. This generation process involves replacing legal jargon with simpler language, creating text that is easily understandable to the user. The output of this step is the detailed legal advice that has been generated.

[0536] Step 5:

[0537] The terminal outputs the legal advice generated in step 4 to the user via an audio output device. It also visually displays the legal advice on a display device. This provides the user with information through both audio and visual means. The output consists of the audioized legal consultation results and the text displayed on the screen.

[0538] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0539] This invention provides a system for realizing a legal consultation agent that combines an emotion engine that recognizes the user's emotions. This system can provide more personalized legal consultations by receiving consultations from users and analyzing their emotions.

[0540] The server incorporates an emotion engine, which not only uses a natural language processing model to analyze the intent behind user input but also uses the emotion engine to identify the user's emotional state. Based on the text data of user input, this system recognizes emotions such as positive, negative, and neutral. For example, if the input is "I am very confused by this situation," the system will analyze the emotion of confusion.

[0541] After an emotion is recognized, the server uses that emotion information to search for appropriate legal databases through a search mechanism, and then uses a generation mechanism to construct an emotion-sensitive response based on the information obtained. This system can adjust the tone and style of the response according to the emotion. For example, if the user is feeling anxious or worried, the response will use more reassuring language.

[0542] Furthermore, the device includes a function that visually displays the generated answers to the user and highlights important information. By viewing these answers, users can obtain specific and practical legal advice tailored to their specific situation.

[0543] Furthermore, based on the user's emotional state identified by the emotion engine, it also includes a function that suggests direct collaboration with experts as needed. For example, for users exhibiting particularly strong anxiety or distress, it can provide the opportunity to receive direct professional support by offering options for consulting with appropriate experts.

[0544] By utilizing this system, legal counseling agents can not only provide legal information but also deliver legal support in a more humane and easily understandable way that is tailored to the user's emotions. In this way, the present invention improves the user's legal counseling experience and provides a new form of legal consultation.

[0545] The following describes the processing flow.

[0546] Step 1:

[0547] Users enter their inquiries through an input interface on their device. For example, they might enter text such as, "I'm feeling anxious about a recent problem at work and would like to know about legal solutions."

[0548] Step 2:

[0549] The terminal converts user input into an appropriate format and sends it to the server. This input data includes the user's direct needs.

[0550] Step 3:

[0551] The server passes the received input data to a natural language processing engine to analyze the text content. Simultaneously, it uses an emotion engine to identify emotions (e.g., anxiety) contained in the user's text.

[0552] Step 4:

[0553] The server uses search mechanisms to retrieve appropriate information from legal databases, reflecting the user's emotional state. By performing emotion-based filtering, it selects more relevant information.

[0554] Step 5:

[0555] The server uses generation tools to construct appropriate responses based on the search results. At this stage, it considers the emotions identified by the emotion engine and adjusts the tone and expression of the response. For example, it might use phrasing that alleviates anxiety.

[0556] Step 6:

[0557] The server sends the assembled response to the terminal. The response is written in polite language tailored to the user.

[0558] Step 7:

[0559] The device visually displays the received responses to the user. This display highlights important information and is designed to be easy for the user to understand.

[0560] Step 8:

[0561] Based on the displayed answers, users can request further explanations or enter new questions. Additional dialogue is possible through interactive means.

[0562] Step 9:

[0563] If the emotion engine identifies a strong emotional response, the server will suggest direct contact with an expert to the user. This suggestion will be made through the contact mechanism if additional expert assistance is needed.

[0564] (Example 2)

[0565] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0566] Traditional legal consultation systems often provide general legal information without considering the user's specific feelings, failing to adequately address the emotional issues they face. As a result, users often lack the necessary information and struggle to reach satisfactory solutions. Furthermore, a lack of proper coordination with experts hindered the provision of prompt and effective support.

[0567] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0568] In this invention, the server includes an input means for receiving user information and determining its intentions and emotions, a search means for searching a data set while considering emotions, and a generation means for generating an emotionally sensitive response. This enables humane legal consultations that are tailored to the user's emotions.

[0569] A "user" refers to an individual or legal entity that uses the system to seek legal advice.

[0570] "Natural language analysis" refers to the technology of understanding the intent and emotions of human speech from text data, and utilizes natural language processing techniques.

[0571] "Input means" refers to an interface or method for receiving text information from a user.

[0572] A "data set" refers to a database or storage device that contains legal information.

[0573] "Search means" refers to a method or apparatus for searching a data set based on specific conditions and extracting relevant information.

[0574] "Generative means" refers to a method or apparatus for creating a response based on extracted information and user sentiment.

[0575] "Display means" refers to a method or device for visually presenting the generated response to the user.

[0576] "Expert collaboration means" refers to methods or devices for connecting users with appropriate experts as needed.

[0577] A "generative AI model" refers to a model that uses artificial intelligence to generate responses that are tailored to the user's emotions.

[0578] A "prompt statement" refers to an input statement used to obtain a specified output from a generative AI model.

[0579] This invention is a legal consultation agent system that takes user emotions into consideration and includes three main components: a server, a terminal, and a user, for performing specific processing.

[0580] The server receives text input of legal consultations from users and has the capability to perform natural language processing on it. This processing uses Python's NLTK and Transformers natural language processing libraries. By identifying the user's intent and emotions from the analysis results, the emotion engine labels the user's emotional state. For example, if a user inputs "I am very confused about this situation," the server labels it with the emotion "confused." This emotion information is used for effective searching within the data set.

[0581] Subsequently, the server extracts legal information based on the user's emotional state from the data set through search mechanisms. For example, SQL or NoSQL technologies are used for the database and information storage. Based on the retrieved information, the server uses a generative AI model to generate a legal response tailored to the user. OpenAI's GPT-3 is used as the generative AI model, and the tone of the response is adjusted according to the user's emotions through prompts. Prompts are instructions that control the output of the generative AI model, and are in the form of, "The user has the following input: 'I am confused about the boundary with my neighbor.' Please provide legally appropriate advice in this situation while also providing reassurance."

[0582] The input data received from the user is smoothly transmitted to the server using a secure communication protocol, and the generated response is visually displayed to the user on the device. This process utilizes the interface within the device, and important information is highlighted using CSS styles. As a result, users can receive specific, practical legal advice that resonates with their emotions.

[0583] Furthermore, the server includes a feature that suggests connecting users with experts, especially those exhibiting strong anxiety or confusion. This connection is facilitated by using APIs that connect to external platforms, presenting users with access links to experts. This is a crucial element in ensuring users can quickly obtain the additional support they need.

[0584] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0585] Step 1:

[0586] The user enters their legal consultation details via a terminal. The user's input is sent to the terminal in text format and then transmitted to the server via a secure protocol. This input process initiates the system's analysis of the user's legal questions and consultation details.

[0587] Step 2:

[0588] The server receives input text from the user and passes it to a natural language processing model to determine intent and emotion. A natural language processing library is used for data analysis; specifically, the input text is tokenized, the context is analyzed, and the emotional state is labeled. The output is data indicating the user's emotional state, such as "confused" or "anxious."

[0589] Step 3:

[0590] Based on the analyzed emotional state, the server searches legal databases and extracts information relevant to the user's situation. The input here is the emotional data obtained in the previous step, and the database search uses queries utilizing SQL or NoSQL. The output is legal information related to the user's intentions and emotions.

[0591] Step 4:

[0592] The server uses a generative AI model to generate user-oriented responses based on search results. Here, legal information and sentiment data are taken as input, and prompts are used to instruct the generative AI model, which then generates responses with adjusted tone. The prompts act as queues for generating sentiment-sensitive responses, resulting in emotionally considerate legal advice responses as output.

[0593] Step 5:

[0594] The terminal visually displays the generated response received from the server to the user. This display uses CSS styles to highlight important parts, making it easy for the user to understand and review all the legal advice. This allows the user to quickly obtain specific and practical legal advice.

[0595] Step 6:

[0596] The server provides options for connecting with a professional if a specific emotional state, particularly anxiety or confusion, is detected. This step involves executing an API that takes the user's emotional data as input to prepare a connection to a professional consultation platform. The output presents access links and booking options for professionals relevant to the user.

[0597] (Application Example 2)

[0598] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0599] Current legal consultation systems often provide information without considering the user's feelings, resulting in inadequate support for users' situations. In particular, when users seek advice on legally important but emotionally complex matters, a response that considers their feelings is needed, rather than simply providing information. Furthermore, smooth coordination with experts tailored to the user's emotional state is required.

[0600] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0601] In this invention, the server includes an input means for receiving consultation content from a user and analyzing its intent and emotions using natural language processing; a search means for searching for legal information sources and extracting relevant information based on the results analyzed by the input means; and a generation means for generating a legal response that takes emotions into consideration based on the information extracted by the search means. This makes it possible to provide legal consultation that is sensitive to the user's emotions.

[0602] An "input method" is an interface that receives information such as voice or text from the user and processes it in a digital format.

[0603] "Natural language processing" is a technology that enables computers to understand, analyze, and generate responses to human language.

[0604] "Emotion analysis" is a technology that identifies emotions from information provided by the user and represents that state using numerical values ​​or text.

[0605] A "search tool" is a function that references a specified information source and quickly and accurately extracts the necessary relevant information.

[0606] "Generation method" refers to the process of constructing a response to the user based on extracted information and analysis results.

[0607] "Display means" refers to devices or technologies used to present results to the user visually or audibly.

[0608] A "collaboration method" refers to a system that proposes connections with suitable experts and other relevant parties, and facilitates the rapid sharing of necessary information.

[0609] A "computational means" is a calculation function that analyzes input data and derives appropriate results.

[0610] This invention relates to a system for providing legal consultations that take into consideration the user's feelings. The system is accessible to the user through various devices and is implemented in the following manner.

[0611] The server uses advanced speech recognition technology and the Google Speech-to-Text API to convert the user's speech into text data. The converted text data is then analyzed using natural language processing techniques. In this process, OpenAI's large-scale language model is used to identify the user's intent and related legal matters.

[0612] Next, sentiment analysis is performed using the analyzed data. This is done using IBM Watson Tone Analyzer, which classifies the user's emotional state as positive, negative, or neutral. Based on this sentiment information, the server appropriately adjusts the tone and style of the legal advice.

[0613] The search system incorporates a mechanism that references legal information sources, allowing for the rapid extraction of important information. The generated answers are displayed via terminals such as robots. These terminals are equipped with displays, allowing users to visually confirm the answers.

[0614] In a real-world example, if a user asks, "I'm worried that my working conditions might be in violation of the law," the system will provide information on relevant labor laws and offer appropriate advice in a friendly and helpful manner. In this way, users can receive legal support tailored to their specific situation.

[0615] Furthermore, if the user's emotional state is very negative, the server will suggest options for connecting with appropriate professionals. This gives the user the opportunity to receive professional support as needed.

[0616] An example of a prompt message would be, "When a user is seeking legal advice that includes emotions, generate advice appropriate to their emotional state and suggest referral to a specialist if necessary." This invention will enable more humane and understandable legal support.

[0617] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0618] Step 1:

[0619] The user provides voice input to the device. The device uses a high-performance microphone to send the information to the server as voice data.

[0620] Step 2:

[0621] The server converts the received audio data into text data using the Google Speech-to-Text API. In this process, the audio signal is converted into digital text information. The output text data is then passed on to the next step.

[0622] Step 3:

[0623] The server uses OpenAI's large-scale language model to analyze the intent behind the text data. This analysis clarifies the legal content of the consultation. The user's intent and related legal items obtained from the analysis are then sent to the next processing step.

[0624] Step 4:

[0625] The server uses IBM Watson Tone Analyzer to analyze emotions from text data. In this step, the data is output as an emotional state (positive, negative, neutral). This emotional information is then used in the next step of generating responses.

[0626] Step 5:

[0627] The server searches for legal information sources based on the analyzed intent and sentiment information. It extracts relevant legal information and provides it for the next step. The search results include relevant legal articles and past case precedents.

[0628] Step 6:

[0629] Based on the information extracted in the previous step, the server generates legal advice that takes the user's emotions into consideration. It utilizes a generative AI model to construct the response with an appropriate tone and phrasing. This response is then formatted for display output.

[0630] Step 7:

[0631] The device presents the user with a formatted response sent from the server. The display visually shows the information and, in some cases, provides audio output. The user sees the response and receives reassuring support based on sensitive information.

[0632] Step 8:

[0633] If the server determines that the user's emotional state is negative and further support is needed, it will suggest an option to consult with a relevant expert. This option connects the user with a suitable expert and allows them to receive direct assistance.

[0634] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0635] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0636] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0637] [Fourth Embodiment]

[0638] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0639] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0640] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0641] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0642] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0643] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0644] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0645] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0646] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0647] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0648] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0649] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0650] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0651] This invention relates to a system that operates as a legal consultation agent, allowing users to input legal questions and receive quick and accurate answers. The system includes input means, search means, generation means, display means, interaction means, and linking means, and these functions efficiently support the user's legal consultation process.

[0652] The server is equipped with a natural language processing model that analyzes text input from users and interprets their intent. Users can input their questions via their terminal, for example, by entering specific questions such as, "Please tell me about divorce procedures." This input is sent to the server via the terminal's input method.

[0653] The server uses search mechanisms to access legal databases and retrieve legal information relevant to the user's question. This information is processed by generation mechanisms to construct an answer tailored to the user's needs. This answer is generated by translating legal jargon into the clearest possible language.

[0654] The terminal displays the answers received from the server to the user. This allows the user to immediately obtain specific advice regarding legal consultations. For example, they can understand the specific documents and legal procedures required for divorce proceedings.

[0655] Furthermore, if users wish to ask additional questions based on the answers provided, they can engage in further dialogue using the interaction tools. Additionally, if specialized legal interpretations are required, the system offers the option to connect with experts in that field using the collaboration tools.

[0656] In this way, this system provides rapid access to legal knowledge and lowers the barrier to seeking legal advice, thereby helping users resolve their legal problems.

[0657] The following describes the processing flow.

[0658] Step 1:

[0659] Users enter specific legal questions through the user interface on their device. For example, they might enter text such as, "Please tell me about the legal procedures regarding inheritance."

[0660] Step 2:

[0661] The terminal prepares the data received from the user into the necessary format for transmission to the server and then transfers it to the server.

[0662] Step 3:

[0663] The server inputs the received text data into a natural language processing model to analyze the intent behind the user's question. This analysis extracts keywords and themes related to the relevant legal domain.

[0664] Step 4:

[0665] The server uses search methods to search legal databases based on extracted keywords and collects relevant legal information and case precedents.

[0666] Step 5:

[0667] The server uses collected legal information and generation tools to construct answers to user questions. During this process, it simplifies terminology and employs techniques to ensure clarity as needed.

[0668] Step 6:

[0669] The server sends the generated response to the terminal. It formats the data into the necessary format for display on the user's terminal.

[0670] Step 7:

[0671] The device displays the received responses to the user. These responses may include a feature to highlight important information.

[0672] Step 8:

[0673] Based on the displayed answers, users can ask additional questions about any further concerns. In this case, they can initiate further discussions using interaction tools.

[0674] Step 9:

[0675] If necessary, users can choose to consult with experts through various means of collaboration. This includes the ability to send connection requests to relevant experts.

[0676] (Example 1)

[0677] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] In legal consultations, there is a need to provide users with an environment where they can obtain information quickly and accurately. Furthermore, a system is needed that allows users to acquire legal information in an easily understandable format and to easily connect with experts as needed. Traditional legal consultations are time-consuming and expensive, and access is limited, posing challenges to efficient information acquisition and consultation.

[0679] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0680] In this invention, the server includes acquisition means for acquiring information from the user and interpreting its intent through natural language processing, query means for querying an information database and extracting relevant information, and assembly means for assembling the information. This allows the user to efficiently acquire legal information, make additional inquiries, and easily collaborate with experts.

[0681] A "user" is someone who uses the system to obtain legal information.

[0682] "Acquisition method" refers to the means of obtaining information from users and incorporating that information into the system.

[0683] "Natural language processing" is a technology that enables computers to understand and process text data written in languages ​​that humans normally use.

[0684] "Interpreting intent" means understanding the meaning of user questions and requests contained in text data and accurately grasping their content.

[0685] A "search method" is a means of searching a database, finding information related to the entered keywords or themes, and retrieving it.

[0686] An "information database" is a collection of information that systematically stores data related to the law.

[0687] "Assembly methods" refer to means of constructing information and answers in a clear and easy-to-understand format for the user, based on the information acquired.

[0688] "Presentation method" refers to a means of showing assembled information or answers to the user.

[0689] A "dialogue mechanism" is a mechanism that allows users to ask more detailed questions or request additional information.

[0690] "Connection means" refers to methods that enable direct communication between users and experts.

[0691] This invention provides a system that delivers legal information quickly and accurately, creating an environment where users can easily seek legal advice. The system is primarily composed of a server and terminals, enabling users to obtain legal information.

[0692] The user enters legal questions through the terminal. For example, the user might enter the question, "Please tell me about divorce procedures," using the terminal's input device. The terminal converts this input into a signal and sends it to the server.

[0693] The server receives the input information and interprets the user's intent using natural language processing techniques. This process employs generative AI models, specifically natural language processing models such as GPT and BERT. This allows the server to accurately understand the question and prepare an appropriate response.

[0694] Based on the interpreted intent, the server queries the information database and retrieves relevant information. This information is stored in a legal database and includes important information and procedural details for the user.

[0695] The acquired information is organized using the server's assembly method and structured in a way that is easy for the user to understand. Even information that frequently uses legal terminology is rephrased and organized in a way that is easy for the user to understand.

[0696] Finally, the server sends this configured information back to the terminal, which then displays it visually to the user. This allows the user to immediately see specific advice and procedural steps regarding legal consultations.

[0697] Furthermore, if a user has additional questions, they can enter them again through the terminal, and the server can repeat the process of receiving these questions and providing new information. For example, if a user enters a prompt such as "Please tell me how to calculate inheritance tax," detailed information will be provided accordingly.

[0698] This system allows users to efficiently obtain legal information and easily connect with experts when advanced consultations are needed.

[0699] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0700] Step 1:

[0701] The user enters legal questions through the terminal. Specifically, the user uses a keyboard or voice input device to enter questions such as, "Please tell me about divorce procedures," and this information is captured by the terminal's input system. The entered data is prepared as formatted text for processing in the next step.

[0702] Step 2:

[0703] The terminal sends the entered question to the server. The data is transmitted over the network, and in this process, the input data is converted into data packets. Specifically, a signal is sent to the server using an internet connection. The server receives this signal and prepares for the next step.

[0704] Step 3:

[0705] The server analyzes the received text data using a natural language processing model. A generative AI model is then used to interpret the intent behind the text. For example, the server uses a GPT model to extract context and keywords to understand the meaning of the user's question. This generates analysis results, which are then converted into a data format for further processing.

[0706] Step 4:

[0707] The server searches the information database based on the analysis results. The server generates database queries and retrieves relevant legal information. Specifically, it extracts data on necessary documents and procedural steps related to "divorce proceedings." During this process, the information is filtered and prioritized.

[0708] Step 5:

[0709] The server assembly method involves structuring the extracted information in a way that is easily understood by the user. Legal terminology is replaced with easily understandable general terms, and explanatory text is constructed. The generated text is prepared in a user-friendly format and converted into a displayable format in the next step.

[0710] Step 6:

[0711] The server sends the generated response to the terminal. The terminal renders the received information on the screen and presents it to the user. The terminal displays the response as easy-to-read text or graphical output, making it ready for immediate use.

[0712] Step 7:

[0713] If the user has further questions, they can use the terminal to make additional inquiries. The terminal will then accept user interaction again and prepare to send a new prompt to the server. This allows the server to start a new processing cycle and answer questions repeatedly.

[0714] (Application Example 1)

[0715] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0716] There is a challenge in providing users with timely and accurate legal information when they need legal advice. Furthermore, even when specialized expertise is required, there is a need for methods that users can easily access. Under these circumstances, there is a demand for providing means that users can easily seek legal advice even within the home.

[0717] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0718] In this invention, the server includes an input means that receives voice input from a user and analyzes its intent using natural language processing; a search means that searches a storage device containing legal information based on the results analyzed by the input means and extracts relevant information; and a generation means that generates a legal response based on the information extracted by the search means and presents it to the user in a form that includes voice output. This enables users to have legal consultations via voice within their homes, obtain information immediately, and use it to solve problems.

[0719] A "user" is an individual who uses this system to seek legal advice.

[0720] "Voice input" is a method of capturing a user's speech as digital data via a microphone or computer terminal.

[0721] "Natural language processing" is a technology that interprets the language spoken naturally by humans and converts it into a format that can be processed by computers.

[0722] A "storage device" is a device that stores legal data and information and makes it accessible as needed.

[0723] A "search function" is a function that searches for data within a storage device according to specified conditions and extracts relevant information.

[0724] "Generation method" refers to the technology that constructs answers to be provided to the user based on the extracted information.

[0725] A "voice output device" is a device that allows the user to hear the generated response, and it uses speech synthesis technology to produce the voice.

[0726] A "display device" is a device used to visually present the generated response to the user.

[0727] Embodiments of the present invention will now be described. Users can consult with legal experts via voice through a consumer robot. This robot is equipped with a voice input means, a natural language processing unit, a legal information storage device, a voice output device, and a display device.

[0728] First, when a user asks a legal question to the robot by voice, the voice input device captures this voice as text data. This input is then interpreted by a natural language processing unit. The natural language processing unit uses a generative AI model to analyze the intent of the user's question.

[0729] Based on the analyzed intent, the server searches the legal information storage device and extracts relevant legal information. This information is then assembled into a user-friendly format through a generation mechanism.

[0730] The compiled legal information is provided to the user verbally via an audio output device. Additionally, detailed information is displayed on a display screen as needed, providing a visual representation to the user.

[0731] For example, if a user asks the robot, "Please tell me about the divorce process," the robot will convert the question from speech to text and search legal databases. It can then find the most relevant information about the divorce process and necessary documents and explain it to the user via voice and display. This entire process is automated and fast.

[0732] An example of a prompt message is, "Please provide legal information regarding divorce proceedings." Through such prompts, the system can provide accurate legal information that meets the user's needs.

[0733] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0734] Step 1:

[0735] The user inputs legal questions into the robot via voice. This voice input is captured by the device through the microphone and converted into text data using speech recognition technology. This text data becomes the input for the next process.

[0736] Step 2:

[0737] The device uses a generative AI model to analyze the intent of text converted from speech. This analysis uses natural language processing techniques to identify the context and key keywords in the text data and extract legal themes. The output of this step is the legal topic inferred based on the user's question.

[0738] Step 3:

[0739] Based on the output of step 2, the server searches the legal information storage device. An efficient search algorithm is used to extract relevant information from the database regarding the specified legal topic. The legal information is the output of this step.

[0740] Step 4:

[0741] The server uses a generative AI model to generate legal answers tailored to the user, based on the acquired legal information. This generation process involves replacing legal jargon with simpler language, creating text that is easily understandable to the user. The output of this step is the detailed legal advice that has been generated.

[0742] Step 5:

[0743] The terminal outputs the legal advice generated in step 4 to the user via an audio output device. It also visually displays the legal advice on a display device. This provides the user with information through both audio and visual means. The output consists of the audioized legal consultation results and the text displayed on the screen.

[0744] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0745] This invention provides a system for realizing a legal consultation agent that combines an emotion engine that recognizes the user's emotions. This system can provide more personalized legal consultations by receiving consultations from users and analyzing their emotions.

[0746] The server incorporates an emotion engine, which not only uses a natural language processing model to analyze the intent behind user input but also uses the emotion engine to identify the user's emotional state. Based on the text data of user input, this system recognizes emotions such as positive, negative, and neutral. For example, if the input is "I am very confused by this situation," the system will analyze the emotion of confusion.

[0747] After an emotion is recognized, the server uses that emotion information to search for appropriate legal databases through a search mechanism, and then uses a generation mechanism to construct an emotion-sensitive response based on the information obtained. This system can adjust the tone and style of the response according to the emotion. For example, if the user is feeling anxious or worried, the response will use more reassuring language.

[0748] Furthermore, the device includes a function that visually displays the generated answers to the user and highlights important information. By viewing these answers, users can obtain specific and practical legal advice tailored to their specific situation.

[0749] Furthermore, based on the user's emotional state identified by the emotion engine, it also includes a function that suggests direct collaboration with experts as needed. For example, for users exhibiting particularly strong anxiety or distress, it can provide the opportunity to receive direct professional support by offering options for consulting with appropriate experts.

[0750] By utilizing this system, legal counseling agents can not only provide legal information but also deliver legal support in a more humane and easily understandable way that is tailored to the user's emotions. In this way, the present invention improves the user's legal counseling experience and provides a new form of legal consultation.

[0751] The following describes the processing flow.

[0752] Step 1:

[0753] Users enter their inquiries through an input interface on their device. For example, they might enter text such as, "I'm feeling anxious about a recent problem at work and would like to know about legal solutions."

[0754] Step 2:

[0755] The terminal converts user input into an appropriate format and sends it to the server. This input data includes the user's direct needs.

[0756] Step 3:

[0757] The server passes the received input data to a natural language processing engine to analyze the text content. Simultaneously, it uses an emotion engine to identify emotions (e.g., anxiety) contained in the user's text.

[0758] Step 4:

[0759] The server uses search mechanisms to retrieve appropriate information from legal databases, reflecting the user's emotional state. By performing emotion-based filtering, it selects more relevant information.

[0760] Step 5:

[0761] The server uses generation tools to construct appropriate responses based on the search results. At this stage, it considers the emotions identified by the emotion engine and adjusts the tone and expression of the response. For example, it might use phrasing that alleviates anxiety.

[0762] Step 6:

[0763] The server sends the assembled response to the terminal. The response is written in polite language tailored to the user.

[0764] Step 7:

[0765] The device visually displays the received responses to the user. This display highlights important information and is designed to be easy for the user to understand.

[0766] Step 8:

[0767] Based on the displayed answers, users can request further explanations or enter new questions. Additional dialogue is possible through interactive means.

[0768] Step 9:

[0769] If the emotion engine identifies a strong emotional response, the server will suggest direct contact with an expert to the user. This suggestion will be made through the contact mechanism if additional expert assistance is needed.

[0770] (Example 2)

[0771] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0772] Traditional legal consultation systems often provide general legal information without considering the user's specific feelings, failing to adequately address the emotional issues they face. As a result, users often lack the necessary information and struggle to reach satisfactory solutions. Furthermore, a lack of proper coordination with experts hindered the provision of prompt and effective support.

[0773] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0774] In this invention, the server includes an input means for receiving user information and determining its intentions and emotions, a search means for searching a data set while considering emotions, and a generation means for generating an emotionally sensitive response. This enables humane legal consultations that are tailored to the user's emotions.

[0775] A "user" refers to an individual or legal entity that uses the system to seek legal advice.

[0776] "Natural language analysis" refers to the technology of understanding the intent and emotions of human speech from text data, and utilizes natural language processing techniques.

[0777] "Input means" refers to an interface or method for receiving text information from a user.

[0778] A "data set" refers to a database or storage device that contains legal information.

[0779] "Search means" refers to a method or apparatus for searching a data set based on specific conditions and extracting relevant information.

[0780] "Generative means" refers to a method or apparatus for creating a response based on extracted information and user sentiment.

[0781] "Display means" refers to a method or device for visually presenting the generated response to the user.

[0782] "Expert collaboration means" refers to methods or devices for connecting users with appropriate experts as needed.

[0783] A "generative AI model" refers to a model that uses artificial intelligence to generate responses that are tailored to the user's emotions.

[0784] A "prompt statement" refers to an input statement used to obtain a specified output from a generative AI model.

[0785] This invention is a legal consultation agent system that takes user emotions into consideration and includes three main components: a server, a terminal, and a user, for performing specific processing.

[0786] The server receives text input of legal consultations from users and has the capability to perform natural language processing on it. This processing uses Python's NLTK and Transformers natural language processing libraries. By identifying the user's intent and emotions from the analysis results, the emotion engine labels the user's emotional state. For example, if a user inputs "I am very confused about this situation," the server labels it with the emotion "confused." This emotion information is used for effective searching within the data set.

[0787] Subsequently, the server extracts legal information based on the user's emotional state from the data set through search mechanisms. For example, SQL or NoSQL technologies are used for the database and information storage. Based on the retrieved information, the server uses a generative AI model to generate a legal response tailored to the user. OpenAI's GPT-3 is used as the generative AI model, and the tone of the response is adjusted according to the user's emotions through prompts. Prompts are instructions that control the output of the generative AI model, and are in the form of, "The user has the following input: 'I am confused about the boundary with my neighbor.' Please provide legally appropriate advice in this situation while also providing reassurance."

[0788] The input data received from the user is smoothly transmitted to the server using a secure communication protocol, and the generated response is visually displayed to the user on the device. This process utilizes the interface within the device, and important information is highlighted using CSS styles. As a result, users can receive specific, practical legal advice that resonates with their emotions.

[0789] Furthermore, the server includes a feature that suggests connecting users with experts, especially those exhibiting strong anxiety or confusion. This connection is facilitated by using APIs that connect to external platforms, presenting users with access links to experts. This is a crucial element in ensuring users can quickly obtain the additional support they need.

[0790] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0791] Step 1:

[0792] The user enters their legal consultation details via a terminal. The user's input is sent to the terminal in text format and then transmitted to the server via a secure protocol. This input process initiates the system's analysis of the user's legal questions and consultation details.

[0793] Step 2:

[0794] The server receives input text from the user and passes it to a natural language processing model to determine intent and emotion. A natural language processing library is used for data analysis; specifically, the input text is tokenized, the context is analyzed, and the emotional state is labeled. The output is data indicating the user's emotional state, such as "confused" or "anxious."

[0795] Step 3:

[0796] Based on the analyzed emotional state, the server searches legal databases and extracts information relevant to the user's situation. The input here is the emotional data obtained in the previous step, and the database search uses queries utilizing SQL or NoSQL. The output is legal information related to the user's intentions and emotions.

[0797] Step 4:

[0798] The server uses a generative AI model to generate user-oriented responses based on search results. Here, legal information and sentiment data are taken as input, and prompts are used to instruct the generative AI model, which then generates responses with adjusted tone. The prompts act as queues for generating sentiment-sensitive responses, resulting in emotionally considerate legal advice responses as output.

[0799] Step 5:

[0800] The terminal visually displays the generated response received from the server to the user. This display uses CSS styles to highlight important parts, making it easy for the user to understand and review all the legal advice. This allows the user to quickly obtain specific and practical legal advice.

[0801] Step 6:

[0802] The server provides options for connecting with a professional if a specific emotional state, particularly anxiety or confusion, is detected. This step involves executing an API that takes the user's emotional data as input to prepare a connection to a professional consultation platform. The output presents access links and booking options for professionals relevant to the user.

[0803] (Application Example 2)

[0804] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0805] Current legal consultation systems often provide information without considering the user's feelings, resulting in inadequate support for users' situations. In particular, when users seek advice on legally important but emotionally complex matters, a response that considers their feelings is needed, rather than simply providing information. Furthermore, smooth coordination with experts tailored to the user's emotional state is required.

[0806] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0807] In this invention, the server includes an input means for receiving consultation content from a user and analyzing its intent and emotions using natural language processing; a search means for searching for legal information sources and extracting relevant information based on the results analyzed by the input means; and a generation means for generating a legal response that takes emotions into consideration based on the information extracted by the search means. This makes it possible to provide legal consultation that is sensitive to the user's emotions.

[0808] An "input method" is an interface that receives information such as voice or text from the user and processes it in a digital format.

[0809] "Natural language processing" is a technology that enables computers to understand, analyze, and generate responses to human language.

[0810] "Emotion analysis" is a technology that identifies emotions from information provided by the user and represents that state using numerical values ​​or text.

[0811] A "search tool" is a function that references a specified information source and quickly and accurately extracts the necessary relevant information.

[0812] "Generation method" refers to the process of constructing a response to the user based on extracted information and analysis results.

[0813] "Display means" refers to devices or technologies used to present results to the user visually or audibly.

[0814] A "collaboration method" refers to a system that proposes connections with suitable experts and other relevant parties, and facilitates the rapid sharing of necessary information.

[0815] A "computational means" is a calculation function that analyzes input data and derives appropriate results.

[0816] This invention relates to a system for providing legal consultations that take into consideration the user's feelings. The system is accessible to the user through various devices and is implemented in the following manner.

[0817] The server uses advanced speech recognition technology and the Google Speech-to-Text API to convert the user's speech into text data. The converted text data is then analyzed using natural language processing techniques. In this process, OpenAI's large-scale language model is used to identify the user's intent and related legal matters.

[0818] Next, sentiment analysis is performed using the analyzed data. This is done using IBM Watson Tone Analyzer, which classifies the user's emotional state as positive, negative, or neutral. Based on this sentiment information, the server appropriately adjusts the tone and style of the legal advice.

[0819] The search system incorporates a mechanism that references legal information sources, allowing for the rapid extraction of important information. The generated answers are displayed via terminals such as robots. These terminals are equipped with displays, allowing users to visually confirm the answers.

[0820] In a real-world example, if a user asks, "I'm worried that my working conditions might be in violation of the law," the system will provide information on relevant labor laws and offer appropriate advice in a friendly and helpful manner. In this way, users can receive legal support tailored to their specific situation.

[0821] Furthermore, if the user's emotional state is very negative, the server will suggest options for connecting with appropriate professionals. This gives the user the opportunity to receive professional support as needed.

[0822] An example of a prompt message would be, "When a user is seeking legal advice that includes emotions, generate advice appropriate to their emotional state and suggest referral to a specialist if necessary." This invention will enable more humane and understandable legal support.

[0823] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0824] Step 1:

[0825] The user provides voice input to the device. The device uses a high-performance microphone to send the information to the server as voice data.

[0826] Step 2:

[0827] The server converts the received audio data into text data using the Google Speech-to-Text API. In this process, the audio signal is converted into digital text information. The output text data is then passed on to the next step.

[0828] Step 3:

[0829] The server uses OpenAI's large-scale language model to analyze the intent behind the text data. This analysis clarifies the legal content of the consultation. The user's intent and related legal items obtained from the analysis are then sent to the next processing step.

[0830] Step 4:

[0831] The server uses IBM Watson Tone Analyzer to analyze emotions from text data. In this step, the data is output as an emotional state (positive, negative, neutral). This emotional information is then used in the next step of generating responses.

[0832] Step 5:

[0833] The server searches for legal information sources based on the analyzed intent and sentiment information. It extracts relevant legal information and provides it for the next step. The search results include relevant legal articles and past case precedents.

[0834] Step 6:

[0835] Based on the information extracted in the previous step, the server generates legal advice that takes the user's emotions into consideration. It utilizes a generative AI model to construct the response with an appropriate tone and phrasing. This response is then formatted for display output.

[0836] Step 7:

[0837] The device presents the user with a formatted response sent from the server. The display visually shows the information and, in some cases, provides audio output. The user sees the response and receives reassuring support based on sensitive information.

[0838] Step 8:

[0839] If the server determines that the user's emotional state is negative and further support is needed, it will suggest an option to consult with a relevant expert. This option connects the user with a suitable expert and allows them to receive direct assistance.

[0840] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0841] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0842] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0843] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0844] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0845] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0846] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0847] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0848] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0849] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0850] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0851] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0852] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0853] 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.

[0854] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0855] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0856] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0857] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0858] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0859] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0860] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0861] The following is further disclosed regarding the embodiments described above.

[0862] (Claim 1)

[0863] An input method for receiving user inquiries and analyzing their intent using natural language processing,

[0864] A search means for searching a legal database based on the results analyzed by the input means and extracting relevant information,

[0865] A generation means that generates a legal response based on the information extracted by the aforementioned search means,

[0866] A system including a display means for presenting the answer created by the generation means to the user.

[0867] (Claim 2)

[0868] The system according to claim 1, further comprising an interaction means that allows the user to input additional questions in response to the answers presented by the display means.

[0869] (Claim 3)

[0870] The system according to claim 1, further comprising a cooperation means that provides the user with an option to connect to a relevant expert when generating an answer using the generation means.

[0871] "Example 1"

[0872] (Claim 1)

[0873] A means for acquiring information from users and interpreting their intent through natural language processing,

[0874] A query means that queries an information database based on the results interpreted by the acquisition means and extracts relevant information,

[0875] Based on the information extracted by the aforementioned inquiry means, an assembly means for assembling information,

[0876] A presentation means for presenting information created by the assembly means to the user,

[0877] A means of communication to accept additional inquiries,

[0878] A system that includes connectivity means to provide options for connecting with experts.

[0879] (Claim 2)

[0880] The system according to claim 1, characterized in that the user can make additional inquiries regarding the information presented by the presentation means.

[0881] (Claim 3)

[0882] The system according to claim 1, characterized in that it provides a connection with experts relevant to the user based on the information generated by the assembly means.

[0883] "Application Example 1"

[0884] (Claim 1)

[0885] An input method that receives voice input from a user and analyzes their intent using natural language processing,

[0886] A search means for searching a storage device containing legal information based on the results analyzed by the input means and extracting relevant information,

[0887] Based on the information extracted by the aforementioned search means, a generation means generates a legal response and presents it to the user in a form including audio output,

[0888] A system including a display means for presenting the answer created by the generation means to the user via a display device and an audio output device.

[0889] (Claim 2)

[0890] The system according to claim 1, further comprising an interaction means that allows the user to input additional voice questions in response to the answers presented by the display means.

[0891] (Claim 3)

[0892] The system according to claim 1, further comprising a cooperation means that provides the user with an option to connect to a relevant expert when generating an answer using the generation means.

[0893] "Example 2 of combining an emotion engine"

[0894] (Claim 1)

[0895] An input means that receives information from the user and determines their intent and emotions through natural language processing,

[0896] A search means that searches a data set considering the emotion determined by the input means and extracts relevant information,

[0897] A generation means that generates an emotionally sensitive response based on the information extracted by the aforementioned search means,

[0898] A display means for presenting the answer created by the generation means to the user,

[0899] A means of collaborating with experts that proposes collaboration with experts based on emotional state,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, further comprising a dialogue means that allows the user to input additional information in response to the answer presented by the display means.

[0903] (Claim 3)

[0904] The system according to claim 1, further comprising a generation AI model utilization means for adjusting the tone according to emotion using a generation model when generating a response in the generation means.

[0905] "Application example 2 when combining with an emotional engine"

[0906] (Claim 1)

[0907] A means of receiving user inquiries and analyzing their intentions and emotions using natural language processing,

[0908] A search means for searching for legal information sources and extracting relevant information based on the results analyzed by the input means,

[0909] A generation means that generates a legal response that takes emotions into consideration, based on the information extracted by the aforementioned search means,

[0910] A display means that presents the response created by the generation means to the user and adjusts the tone and manner of speech according to the user's emotions,

[0911] A collaborative mechanism that suggests connecting the user to a suitable expert based on their emotional state,

[0912] A system equipped with computational means specifically designed for emotion analysis.

[0913] (Claim 2)

[0914] The system according to claim 1, which has a function that allows the user to input additional questions in response to the answer presented by the display means and to provide a revised answer based on sentiment analysis.

[0915] (Claim 3)

[0916] The system according to claim 1, which, when generating an answer using the generation means, includes a linkage function that transfers the content of the consultation along with emotional information to relevant experts based on the user's emotional state. [Explanation of Symbols]

[0917] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for receiving user inquiries and analyzing their intent using natural language processing, A search means for searching a legal database based on the results analyzed by the input means and extracting relevant information, A generation means that generates a legal response based on the information extracted by the aforementioned search means, A system including a display means for presenting the answer created by the generation means to the user.

2. The system according to claim 1, further comprising an interaction means that allows the user to input additional questions in response to the answers presented by the display means.

3. The system according to claim 1, further comprising a cooperation means that provides the user with an option to connect to a relevant expert when generating an answer using the generation means.

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