system

Abstract

We provide the system. [Solution] A means of obtaining user voice input, A means for converting the aforementioned voice input into text data using speech recognition technology, A means for analyzing the aforementioned text data using natural language processing technology to identify legal keywords and contexts, A means of querying legal databases and past case databases based on the analysis results and extracting relevant legal information, A means of generating voice responses to legal consultations for users using speech synthesis technology based on extracted legal information, A means of providing the generated response to the user device via voice, A system that includes this.

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, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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] Legal consultations are usually expensive and require scheduling for the consultation, so it is difficult for many people to easily use legal services. In addition, there is a problem that legal terms and procedures are complicated, and general people without specialized knowledge are accompanied by a sense of uneasiness about legal consultations. Therefore, there is a need for a system that can provide legal consultations quickly, at a low price, and in a form that is easy for users to understand.

Means for Solving the Problems

[0005] This invention provides a system that efficiently receives legal consultations from users, analyzes their content using natural language processing technology, and extracts appropriate information from relevant legal databases and past case databases to provide prompt and appropriate legal advice. In particular, it features the ability to convert the generated legal advice into simple language using natural language generation technology, making it easy for users to understand. Furthermore, by linking with legal databases such as the complete collection of Japanese laws and case law databases, it is equipped with the function of providing more accurate legal information.

[0006] A "user terminal" refers to an electronic device used by a user to input and transmit information related to legal consultations.

[0007] "Legal-related input information" refers to text data related to user questions or situations concerning the law.

[0008] "Natural language processing technology" refers to the technology that enables computers to understand and analyze human language.

[0009] "Legal keywords and context" refers to specific legal terms and related phrases and expressions that indicate their meanings.

[0010] A "legal database" refers to a database that stores legal information such as legal articles and precedents.

[0011] A "past case database" refers to a database that stores information on past legal consultations and their solutions.

[0012] "Legal information" refers to legal provisions, precedents, interpretations, and related information concerning the law.

[0013] "Natural language generation technology" refers to the technology that enables computers to generate natural language that is easy for humans to understand.

[0014] The term "Roppo Zensho" refers to a legal text that compiles the major laws of Japan.

[0015] "Case Database" refers to a database that accumulates past judicial judgments and precedents.

[0016] "Means for generating an answer" refers to a process or device that forms legal advice to be provided to the user based on the analyzed information.

Brief Description of Drawings

[0017] [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 Embodiment 2 when a sentiment engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when a sentiment engine is combined.

Mode for Carrying Out the Invention

[0018] 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.

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

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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.

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

[0022] In the following embodiments, the numbered 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.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

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

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0032] 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.

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

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention is an information processing system for providing legal consultations efficiently and at a low cost. Specific embodiments are shown below.

[0039] The user begins by entering their legal questions or concerns into their device. The entered data is sent from the device to the server. The server uses natural language processing techniques to analyze this received data. This analysis identifies legal keywords and context. This step lays the foundation for determining which legal field (e.g., contracts, divorce, inheritance, etc.) the user's question relates to.

[0040] Next, the server queries legal databases and past case databases based on the identified keywords. This extracts information from relevant legal provisions, precedents, and similar past legal consultation cases. The server also connects with legal codes and case law databases to obtain the most accurate and comprehensive legal information possible.

[0041] Next, the server uses natural language generation technology to generate easy-to-understand legal advice answers based on the extracted legal information. The generated answers are designed to avoid technical jargon as much as possible and are presented in a way that is easy for the average user to understand. For example, it can explain the specific steps involved in inheritance procedures, such as "checking the will" and "creating an inheritance division agreement."

[0042] The generated response is sent from the server to the user's device. The device receives this response and displays it in an easy-to-understand interface. This allows the user to receive quick legal advice and smoothly decide on the next steps.

[0043] As a concrete example of this system, consider a case where a user seeks advice regarding divorce procedures. The user inputs "I want to know how to calculate property division in the event of divorce" through their terminal. The server analyzes this information, extracts relevant legal information, and generates advice such as "Property division should be decided through discussions between the spouses, and is generally divided based on the degree to which each person contributed to the formation and maintenance of the assets," which is then provided to the user.

[0044] As described above, the present invention provides a means for users to receive simple and prompt legal consultation, and is a system that makes legal support more accessible.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] Users input legal questions and inquiries into the terminal. For example, they might write specific details in the form, such as "How should I deal with deficiencies in a contract?" The terminal converts the entered data into the appropriate format and sends it to the server.

[0048] Step 2:

[0049] The server receives data sent from the terminal. It passes the received data to a natural language processing module, which then begins analysis. During this process, keywords and important contextual elements within the text are identified, and it is determined which legal field they relate to.

[0050] Step 3:

[0051] The server searches its internal legal database and past case database based on keywords identified through analysis. It refers to relevant legal provisions, precedents, and similar past consultations to extract important information. In doing so, it utilizes legal texts and case law databases to gather as much information as possible.

[0052] Step 4:

[0053] The server uses natural language generation technology to create user-friendly answers based on the collected legal information. The answers avoid legal jargon as much as possible and are written in language that is easy for general users to understand. For example, it might generate advice such as, "If there are deficiencies in the contract, it is advisable to create a revised agreement after discussions with the other party."

[0054] Step 5:

[0055] The server sends the generated response to the user's device. The transmitted data is formatted in a user-readable format by the device's interface.

[0056] Step 6:

[0057] The device notifies the user that the answer has been displayed and provides clear information for the user to take the necessary legal action. At this stage, the user can determine the next steps based on the consultation and take action.

[0058] (Example 1)

[0059] 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."

[0060] When seeking legal advice, users often face challenges such as the complexity of legal terminology and the difficulty of obtaining information quickly. As a result, consulting a legal professional can be time-consuming and expensive. Therefore, there is a need to provide a means for users to access legal advice easily and quickly.

[0061] 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.

[0062] In this invention, the server includes means for acquiring legal information from a user device, means for analyzing the information using language processing technology to identify legal indicators and background information, and means for referencing a legal information base and a past case information base based on the analysis results to retrieve relevant legal information. This makes it possible for users to obtain necessary legal information simply and efficiently without having to understand complex technical terms.

[0063] A "user device" is a terminal device used by a user to send and receive input information.

[0064] "Means of acquiring information" refers to the processes and technologies used by a server to receive legal information transmitted from a user device.

[0065] "Language processing technology" refers to techniques for analyzing natural language text and extracting meaning and keywords from it.

[0066] "Legal indicators and background" refers to key legal terms identified from user input information and the context behind them.

[0067] A "legal information base" is a database that contains official legal information such as legal provisions and precedents.

[0068] A "past case information base" is a database containing a collection of similar legal consultations and precedents from the past.

[0069] "Means of extracting information" refers to the process or technology of searching for and extracting relevant information from legal information databases and past case information databases based on specified conditions.

[0070] This invention is an information processing system that enables users to receive legal advice easily and quickly. A specific embodiment thereof is described below.

[0071] Users input legal questions and inquiries in text format using devices such as smartphones and personal computers. This input data is transmitted from the device to the server via a secure communication protocol (e.g., HTTPS).

[0072] The server uses state-of-the-art natural language processing techniques to analyze the received text data. Specifically, it employs language models such as BERT and generative AI models (e.g., GPT) to extract legal keywords and contextual information from the user's questions. This allows the server to identify which legal field the question relates to.

[0073] Next, the server references a legal information database and a past case information database based on the specified legal field. This database contains legal articles, precedents, and past consultation cases, and the necessary information can be searched and extracted using methods such as SQL queries.

[0074] Based on the extracted legal information, the server uses a generative AI model to create answers for the user. The generated text is simplified, avoiding technical jargon, and presented in a format easily understood by the average user. For example, if a user enters "Tell me about inheritance procedures," the server will generate a response such as "A detailed guide on how to check a will and how to create an inheritance division agreement."

[0075] Finally, the server resends the generated response to the user's device. The device receives this response and displays it visually in an easy-to-understand format on the user interface. This allows the user to obtain quick and detailed legal advice and appropriately decide on the next steps based on their situation and requirements.

[0076] A concrete example of a prompt message would be something like, "I want to create a contract, what should I be careful about?"

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The user uses a terminal to input legal questions. An example input might be, "How is property division calculated during divorce?" This text data is entered on the terminal and sent to the server via the internet. The output from the terminal is the text data entered by the user.

[0080] Step 2:

[0081] The server receives text data sent from the terminal. The received data is raw natural language information. Based on this input data, the server begins analysis using natural language processing techniques. The input is legal text from the terminal, and the output is data with identified legal keywords and context. Specifically, the server extracts the relationship between keywords such as "divorce" and "property division" and their background from the text.

[0082] Step 3:

[0083] The server uses the analyzed data to query the legal information base and the historical case information base. In this step, information in the identified legal field is searched, and relevant legal articles and precedents are retrieved. The input is the analyzed keyword data, and the output is a set of relevant legal information. For example, legal provisions related to property division in divorce cases may be extracted.

[0084] Step 4:

[0085] The server uses a generative AI model to generate user-friendly answers based on the legal information it retrieves through searches. The input is extracted legal information, and the output is a user-friendly answer. For example, it might generate a specific answer such as, "Property division usually recommends dividing assets accumulated jointly by a married couple based on certain criteria."

[0086] Step 5:

[0087] The server sends the generated response to the user's terminal. The server transfers the generated text to the terminal via the internet. The input is the generated response text, and the output is data ready for display on the terminal.

[0088] Step 6:

[0089] The terminal receives legal responses sent from the server and displays them on the user interface. Users can review the visually represented information and use it as a reference to decide on their next course of action. The input is the response data from the server, and the output is the legal information displayed to the user.

[0090] (Application Example 1)

[0091] 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."

[0092] Providing legal consultation services in a more efficient and convenient manner is a crucial challenge in modern society. Traditional methods often involve complex legal terminology, making them difficult for users without specialized knowledge to access. Furthermore, direct consultations with experts are time-consuming and costly, making them inaccessible to many. Additionally, legal consultation systems utilizing voice input are underdeveloped, highlighting the need for a system that can provide appropriate and prompt legal answers based on user voice input.

[0093] 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.

[0094] In this invention, the server includes means for converting user voice input into text data using speech recognition technology, means for analyzing the text data using natural language processing technology to identify legal keywords and context, and means for querying a legal database and a past case database based on the analysis results to generate a legal consultation response in voice. This makes it possible to quickly obtain legal information using voice and to receive legal consultation in a format that is easy for the user to understand.

[0095] "Voice input" refers to information provided by users via voice for legal consultation.

[0096] "Speech recognition technology" is a technology that converts voice signals from a user into text format.

[0097] "Text data" refers to string data converted through speech recognition technology.

[0098] "Natural language processing technology" is a technique used to analyze text data and identify legal keywords and contexts.

[0099] "Legal keywords" are words or phrases that have significant meaning in legal documents or legal consultations.

[0100] "Context" refers to the surrounding words and sentences that determine the meaning of a keyword in text data.

[0101] A "legal database" is a system that stores and maintains laws and legal documents in a searchable format.

[0102] A "past case database" is a system that accumulates and manages cases that have been previously handled legally, allowing them to be referenced for similar legal issues.

[0103] "Speech synthesis technology" is a technology that converts text data of legal consultations into speech and uses it to respond to users.

[0104] "Legal advice answers" refer to advice or information generated based on a user's legal-related question.

[0105] A "user device" is an electronic device used by a user to input legal consultations and output responses.

[0106] This invention provides a system that efficiently delivers legal advice to users using voice, by combining speech recognition technology and natural language processing technology. This system is configured to operate appropriately at each stage of voice input acquisition, analysis, response generation, and response delivery. The hardware and software used, and their operation, are described below.

[0107] First, the user inputs a legal question via voice from their device through a specific operation. This voice data is converted into text data using software that performs speech recognition technology. Google® Cloud Speech-to-Text is used here. This converted text data is then sent to a server.

[0108] The server analyzes the received text data using a natural language processing engine. Here, SpaCy is used to identify legal keywords and context from within the text. Based on the analysis results, the server accesses legal databases and past case databases via SQLite to extract relevant legal information.

[0109] Next, based on the extracted legal information, speech synthesis technology is used to generate legal advice answers for the user. Google Text-to-Speech is used for this process, and the generated audio data is sent to the user's device. This device provides the generated audio to the user, allowing the user to receive legal advice answers in a manner similar to that of a human expert.

[0110] For example, if a user asks a question related to divorce proceedings via voice, the terminal can convert the voice into text, and the server can analyze it to generate advice such as, "Property division should be based on an agreement between the spouses and should be divided considering the degree to which each party contributed to the creation and maintenance of the assets." An example of the prompt text in this case is as follows:

[0111] Example of a prompt:

[0112] "I would like to consult about property division in a divorce."

[0113] In this way, users can receive legal advice in an efficient and easy-to-understand manner.

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The user inputs their legal consultation question via voice into their device. The device then converts this voice into text data using Google Cloud Speech-to-Text. This conversion process yields text output from an input in the form of an audio signal.

[0117] Step 2:

[0118] The terminal sends the converted text data to the server. The server receives this text data and performs analysis using natural language processing techniques. Specifically, it uses SpaCy to identify legal-related keywords and context from the input text. This generates a keyword list as output from the text data input.

[0119] Step 3:

[0120] The server uses specified keywords to query legal databases and past case databases using SQLite. A keyword list is used as input to extract relevant legal information. This results in output in the form of response materials based on the database information.

[0121] Step 4:

[0122] The server uses natural language generation technology to prepare user-friendly legal advice answers based on extracted legal information. Google Text-to-Speech is used to convert the text-based answers into audio. In this process, audio data is generated from the input answer materials.

[0123] Step 5:

[0124] The server sends the generated audio data to the user's terminal. The terminal plays the audio data and provides the user with answers to their legal questions. The user receives input in the form of audio data and can receive legal advice by listening to the output.

[0125] This series of processes enables efficient legal consultations utilizing voice input.

[0126] 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.

[0127] This invention aims to improve the method of responding to users' legal consultations and provides an advanced information processing system incorporating an emotion engine. Specific embodiments are shown below.

[0128] First, the user enters their legal consultation details or questions into the device using natural language. The information entered by the user is sent from the device to the server. The server receives this data and first uses an emotion engine to analyze the user's emotions from the input text. Based on keywords and sentence structure in the text, the emotion engine identifies the emotions the user is likely feeling (e.g., anxiety, anger, relief).

[0129] After recognizing emotions, the server uses natural language processing technology to analyze the input information and identify legal keywords and context. Based on this analysis, the server queries legal databases and past case databases. The databases are linked to legal texts and case law databases, and relevant materials are referenced to extract the necessary legal information.

[0130] Next, the server uses natural language generation technology to generate a response for the user based on the extracted legal information. During this generation process, the tone and content of the response are adjusted according to the recognized emotions of the user. For example, if the user is feeling anxious, the response addresses this by using reassuring language and clearly outlining the steps to take. Furthermore, additional support information and words of comfort may be added to address the user's emotions.

[0131] The generated responses are sent from the server to the user's terminal and displayed in a user-friendly interface. This allows users to receive legal advice easily and with peace of mind.

[0132] As a concrete example, suppose a user seeks legal advice regarding a workplace problem. From the entered text, the emotion engine identifies signs of strong anxiety and stress in the user. The server takes this emotional information into consideration and provides advice on appropriate legal procedures, while also adding reassuring messages such as, "Please rest assured. You are fully protected by the law."

[0133] This system aims to comprehensively improve the accuracy of legal consultations and the user experience, thereby providing a better service.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The user enters their legal consultation question into the terminal in natural language. For example, they might enter, "I want to know about the legal response to a workplace dispute." The terminal converts this input data into the appropriate format and sends it to the server.

[0137] Step 2:

[0138] The server receives data sent from the terminal. The received data is first sent to the emotion engine, which analyzes the user's emotions from the input text. For example, it identifies the level of anxiety or stress the user is feeling from the tone of voice and keywords in the text.

[0139] Step 3:

[0140] The server analyzes the data using natural language processing techniques, taking into account the emotions identified by the emotion engine. It extracts legal keywords and context, and uses this to understand the user's consultation content.

[0141] Step 4:

[0142] The server queries legal databases and past case databases based on the analyzed information. This extracts necessary legal information from relevant legal provisions, precedents, and past consultation cases. The server also works in conjunction with legal code databases and case law databases to obtain accurate data.

[0143] Step 5:

[0144] The server generates responses using natural language generation technology based on extracted legal information, adjusting the content of the responses according to the perceived emotions of the user. To alleviate anxiety and stress, reassuring expressions and specific action steps can be added to the responses.

[0145] Step 6:

[0146] The server sends the generated response to the user's device. The transmitted data is displayed on the device in a format that is easy for the user to understand.

[0147] Step 7:

[0148] The device presents the user with the answer, allowing the user to take appropriate legal action based on that information. The user can then consider the next steps with a sense of security.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] Traditional legal consultation systems suffered from problems such as a lack of emotional consideration in the legal advice provided to users, and the use of complex and difficult-to-understand legal terminology. This led to users feeling anxious and being unable to fully utilize the information provided. Furthermore, insufficient integration between legal databases and past case databases posed a risk of reduced information accuracy.

[0152] 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.

[0153] In this invention, the server includes means for receiving legal input data from a user terminal, means for analyzing the input data using natural language processing technology to identify relevant terms and contexts, and means for adjusting the tone of advice based on the analyzed emotional elements. This enables the provision of emotionally sensitive and easy-to-understand legal advice, allowing users to use the system with confidence.

[0154] A "user terminal" is an electronic device that users directly operate to provide legal-related input data.

[0155] "Input data" refers to information provided by the user for legal consultation, and is typically text data expressed in natural language.

[0156] "Natural language processing technology" is a technology that enables computers to understand and appropriately analyze human language.

[0157] "Relevant terms and context" refers to words and phrases that are considered important in legal consultations, as well as the background situation and meaning behind them.

[0158] A "knowledge base" is a collection of data, including legal information and case precedents, that is used to provide appropriate legal advice.

[0159] "Emotional elements" refer to the emotional characteristics that users express in their input data, and include emotional states such as anxiety and reassurance.

[0160] "Legal advice" refers to solutions and guidelines provided to users in response to their legal inquiries, and is information generated to help users understand the subject.

[0161] The "tone of advice" refers to the way legal advice is expressed and the tone of voice, which is adjusted according to the user's emotions.

[0162] This system efficiently and emotionally supports users in seeking legal advice. The user begins by entering their legal consultation or question in natural language into their terminal. The user's terminal then sends the input data to a server. This transmission process typically utilizes the internet, and encryption technology is used to ensure secure data transmission.

[0163] The server uses natural language processing techniques to analyze the received input data. This technique identifies important legal terms and contexts. Morphological and contextual analysis algorithms are typically used for the analysis. Next, the server consults a knowledge base to extract legal information relevant to the input data. The knowledge base includes comprehensive legal codes and case law, and this information forms the basis for legal advice to the user.

[0164] Furthermore, the server also takes emotional factors into account. Using an emotion engine, it analyzes and identifies the emotions expressed by the user. Emotions such as anxiety, anger, and relief are extracted from the data, and the tone of the legal advice provided is adjusted accordingly.

[0165] As a concrete example, consider a case where a user enters, "I need advice regarding sexual harassment at work. I'm feeling anxious." The server analyzes this input, collecting legally relevant information while simultaneously recognizing the user's anxiety. Based on this, it generates advice in a tone such as, "Your rights are protected by law. Please rest assured," and sends it to the user's device.

[0166] This system uses a generative AI model to provide users with a safe and secure environment for legal consultations. Examples of prompts include, "I want legal advice regarding a workplace problem. What procedures should I follow?" In this way, users can receive support to address legal issues quickly and effectively.

[0167] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0168] Step 1:

[0169] The user inputs legal advice or questions into the terminal using natural language. The input data from the user is in text format, and the terminal receives this data and prepares to send it to the server. This step forms the basis for information gathering by the user.

[0170] Step 2:

[0171] The terminal sends input data received from the user to the server. The transmitted data is securely encrypted and delivered to the server via the internet connection. A special communication protocol is used during this process to maintain data integrity.

[0172] Step 3:

[0173] The server receives input data sent from the terminal and begins analysis using natural language processing techniques. The text data received as input is broken down by morphological analysis, and legal terms and related keywords are extracted. The analyzed information is then used for querying in the next step.

[0174] Step 4:

[0175] The server searches a knowledge base based on the analyzed keywords and contextual information. This knowledge base includes legal codes and case law data, serving as a foundation for querying relevant legal information. As output, legal information related to the user's inquiry is extracted and proceeds to the next generation process.

[0176] Step 5:

[0177] The server uses an emotion engine to analyze the user's emotional elements from the input data. Here, it identifies the user's emotions from the linguistic structure and vocabulary within the text, extracting emotional characteristics such as anxiety and reassurance. As output, this emotional information is used in the advice generation process.

[0178] Step 6:

[0179] The server generates legal advice using natural language generation technology, based on pre-extracted legal and emotional information. During this generation process, it adjusts the tone according to the user's emotions while constructing appropriate advice. The output is legal advice presented in a format that is easy for the user to understand.

[0180] Step 7:

[0181] The generated legal advice is sent from the server to the user's terminal. The user can receive this advice on their terminal and use it to assist in their legal consultation. The display interface is designed to make the advice easy for the user to read.

[0182] (Application Example 2)

[0183] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0184] When users seek legal advice, it is essential to provide appropriate legal advice based solely on the content of their inquiry. However, responses that disregard the user's emotional state can hinder the user experience. Traditional legal consultation systems focus on providing legal information but lack consideration for the user's emotional needs. Therefore, it is necessary to enhance user confidence and trust by appropriately adjusting legal consultation responses to the user's emotions.

[0185] 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.

[0186] In this invention, the server includes means for receiving legal-related input information from the user, means for analyzing the input information using natural language processing technology to identify legal-related keywords and context, and sentiment analysis technology for analyzing the user's emotions from the input information. This makes it possible to provide consistent legal consultation that takes into account not only the user's legal needs but also their emotional state.

[0187] A "user terminal" is a computer device used by users to input the details of their legal consultation and communicate with the server.

[0188] "Natural language processing technology" is a technique for converting text data into a form that computers can understand and then analyzing it.

[0189] "Legal keywords and context" refers to important legal terms and their meanings found within the input information.

[0190] "Emotion analysis technology" is a technology that identifies and analyzes emotions from text input by users.

[0191] A "legal database" is a collection of electronic data containing legal information such as legal codes and precedents.

[0192] "Natural language generation technology" is a technology that generates sentences that are natural and easy for humans to understand, based on information that a computer has understood.

[0193] "Legal consultation answers" refer to solutions and advice provided to users regarding their legal questions and problems.

[0194] "User-appropriate tone" refers to a tone and expression that is appropriate to the user's emotions and situation.

[0195] This invention describes embodiments for carrying out this invention. This system is configured with a server at its core that interacts with a user terminal for legal consultation. When a user inputs legal consultation information into the user terminal, that information is sent to the server. The server first analyzes the input information using natural language processing technology to identify legal-related keywords and context. For example, a computing device running an NLP library is used for this purpose.

[0196] Next, the user's emotions are analyzed using emotion analysis technology. This analysis utilizes emotion analysis engines (e.g., IBM Watson®, Google Cloud Natural Language API) to extract emotions from the input text. Once emotions are identified, legal databases and past case databases are queried based on the analysis results to extract relevant legal information. This involves using database software that includes legal codes and case law data.

[0197] Based on extracted legal information and sentiment analysis results, natural language generation technology is used to generate legal advice responses in a tone appropriate to the user. The generated responses are sent to the user's terminal and displayed. A natural language generation engine (e.g., OpenAI®'s GPT series) is used in this process.

[0198] As a concrete example, consider a case where a user enters a legal consultation request stating, "I am worried about a problem at work." The system senses this anxiety and generates appropriate, emotionally responsive advice such as, "The problem is protected by law, so please rest assured. Here's how you should proceed next." In this way, the system considers the user's emotions during the legal consultation process, enabling it to provide more humane and reliable responses.

[0199] An example of a prompt for the generating AI model is as follows: "The user is expressing concern about noise problems with their neighbor. Please generate a response that provides reassurance while also outlining legal solutions."

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The user inputs the content of their legal consultation into their terminal using natural language. The entered text information is sent directly to the server, so the primary input is the legal consultation text. The output is the text sent to the server.

[0203] Step 2:

[0204] The server analyzes the received text information using natural language processing (NLP) techniques. Specifically, it uses an NLP library to extract legal keywords and context. This process outputs specific terms related to the legal context.

[0205] Step 3:

[0206] The server analyzes the user's emotions using emotion analysis technology based on the parsed text information. Specifically, it uses an emotion analysis engine to identify emotions such as "anxiety," "relief," and "anger." The output of this process is data indicating the user's emotions.

[0207] Step 4:

[0208] The server queries legal databases and past case databases using legal keywords and sentiment data. It extracts appropriate legal information from the databases and outputs the relevant information.

[0209] Step 5:

[0210] The server uses extracted legal information and sentiment data to generate legal advice responses for the user using natural language generation technology. This process utilizes a generative AI model to create output that corresponds to the prompt text. The generated responses have a tone that matches the user's emotions.

[0211] Step 6:

[0212] The server sends the generated response to the user's terminal. The output response is presented to the user through the user interface, allowing the user to visually confirm it.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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".

[0229] This invention is an information processing system for providing legal consultations efficiently and at a low cost. Specific embodiments are shown below.

[0230] The user begins by entering their legal questions or concerns into their device. The entered data is sent from the device to the server. The server uses natural language processing techniques to analyze this received data. This analysis identifies legal keywords and context. This step lays the foundation for determining which legal field (e.g., contracts, divorce, inheritance, etc.) the user's question relates to.

[0231] Next, the server queries legal databases and past case databases based on the identified keywords. This extracts information from relevant legal provisions, precedents, and similar past legal consultation cases. The server also connects with legal codes and case law databases to obtain the most accurate and comprehensive legal information possible.

[0232] Next, the server uses natural language generation technology to generate easy-to-understand legal advice answers based on the extracted legal information. The generated answers are designed to avoid technical jargon as much as possible and are presented in a way that is easy for the average user to understand. For example, it can explain the specific steps involved in inheritance procedures, such as "checking the will" and "creating an inheritance division agreement."

[0233] The generated response is sent from the server to the user's device. The device receives this response and displays it in an easy-to-understand interface. This allows the user to receive quick legal advice and smoothly decide on the next steps.

[0234] As a concrete example of this system, consider a case where a user seeks advice regarding divorce procedures. The user inputs "I want to know how to calculate property division in the event of divorce" through their terminal. The server analyzes this information, extracts relevant legal information, and generates advice such as "Property division should be decided through discussions between the spouses, and is generally divided based on the degree to which each person contributed to the formation and maintenance of the assets," which is then provided to the user.

[0235] As described above, the present invention provides a means for users to receive simple and prompt legal consultation, and is a system that makes legal support more accessible.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] Users input legal questions and inquiries into the terminal. For example, they might write specific details such as "How should I deal with deficiencies in a contract?" in the form. The terminal converts the entered data into the appropriate format and sends it to the server.

[0239] Step 2:

[0240] The server receives data sent from the terminal. It passes the received data to a natural language processing module, which then begins analysis. During this process, keywords and important contextual elements within the text are identified, and it is determined which legal field they relate to.

[0241] Step 3:

[0242] The server searches its internal legal database and past case database based on keywords identified through analysis. It refers to relevant legal provisions, precedents, and similar past consultations to extract important information. In doing so, it utilizes legal texts and case law databases to gather as much information as possible.

[0243] Step 4:

[0244] The server uses natural language generation technology to create user-friendly answers based on the collected legal information. The answers avoid legal jargon as much as possible and are written in language that is easy for general users to understand. For example, it might generate advice such as, "If there are deficiencies in the contract, it is advisable to create a revised agreement after discussions with the other party."

[0245] Step 5:

[0246] The server sends the generated response to the user's device. The transmitted data is formatted in a user-readable format by the device's interface.

[0247] Step 6:

[0248] The device notifies the user that the answer has been displayed and provides clear information for the user to take the necessary legal action. At this stage, the user can determine the next steps based on the consultation and take action.

[0249] (Example 1)

[0250] 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."

[0251] When seeking legal advice, users often face challenges such as the complexity of legal terminology and the difficulty of obtaining information quickly. As a result, consulting a legal professional can be time-consuming and expensive. Therefore, there is a need to provide a means for users to access legal advice easily and quickly.

[0252] 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.

[0253] In this invention, the server includes means for acquiring legal information from a user device, means for analyzing the information using language processing technology to identify legal indicators and background information, and means for referencing a legal information base and a past case information base based on the analysis results to retrieve relevant legal information. This makes it possible for users to obtain necessary legal information simply and efficiently without having to understand complex technical terms.

[0254] A "user device" is a terminal device used by a user to send and receive input information.

[0255] "Means of acquiring information" refers to the processes and technologies used by a server to receive legal information transmitted from a user device.

[0256] "Language processing technology" refers to techniques for analyzing natural language text and extracting meaning and keywords from it.

[0257] "Legal indicators and background" refers to key legal terms identified from user input information and the context behind them.

[0258] A "legal information base" is a database that contains official legal information such as legal provisions and precedents.

[0259] A "past case information base" is a database containing a collection of similar legal consultations and precedents from the past.

[0260] "Means of extracting information" refers to the process or technology of searching for and extracting relevant information from legal information databases and past case information databases based on specified conditions.

[0261] This invention is an information processing system that enables users to receive legal advice easily and quickly. A specific embodiment thereof is described below.

[0262] Users input legal questions and inquiries in text format using devices such as smartphones and personal computers. This input data is transmitted from the device to the server via a secure communication protocol (e.g., HTTPS).

[0263] The server uses state-of-the-art natural language processing techniques to analyze the received text data. Specifically, it employs language models such as BERT and generative AI models (e.g., GPT) to extract legal keywords and contextual information from the user's questions. This allows the server to identify which legal field the question relates to.

[0264] Next, the server references a legal information database and a past case information database based on the specified legal field. This database contains legal articles, precedents, and past consultation cases, and the necessary information can be searched and extracted using methods such as SQL queries.

[0265] Based on the extracted legal information, the server uses a generative AI model to create answers for the user. The generated text is simplified, avoiding technical jargon, and presented in a format easily understood by the average user. For example, if a user enters "Tell me about inheritance procedures," the server will generate a response such as "A detailed guide on how to check a will and how to create an inheritance division agreement."

[0266] Finally, the server resends the generated response to the user's device. The device receives this response and displays it visually in an easy-to-understand format on the user interface. This allows the user to obtain quick and detailed legal advice and appropriately decide on the next steps based on their situation and requirements.

[0267] A concrete example of a prompt message would be something like, "I want to create a contract, what should I be careful about?"

[0268] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0269] Step 1:

[0270] The user uses a terminal to input legal questions. An example input might be, "How is property division calculated during divorce?" This text data is entered on the terminal and sent to the server via the internet. The output from the terminal is the text data entered by the user.

[0271] Step 2:

[0272] The server receives text data sent from the terminal. The received data is raw natural language information. Based on this input data, the server begins analysis using natural language processing techniques. The input is legal text from the terminal, and the output is data with identified legal keywords and context. Specifically, the server extracts the relationship between keywords such as "divorce" and "property division" and their background from the text.

[0273] Step 3:

[0274] The server uses the analyzed data to query the legal information base and the historical case information base. In this step, information in the identified legal field is searched, and relevant legal articles and precedents are retrieved. The input is the analyzed keyword data, and the output is a set of relevant legal information. For example, legal provisions related to property division in divorce cases may be extracted.

[0275] Step 4:

[0276] The server uses a generative AI model to generate user-friendly answers based on the legal information it retrieves through searches. The input is extracted legal information, and the output is a user-friendly answer. For example, it might generate a specific answer such as, "Property division usually recommends dividing assets accumulated jointly by a married couple based on certain criteria."

[0277] Step 5:

[0278] The server sends the generated response to the user's terminal. The server transfers the generated text to the terminal via the internet. The input is the generated response text, and the output is data ready for display on the terminal.

[0279] Step 6:

[0280] The terminal receives the legal answer sent from the server and displays it on the user interface. The user can check the visually presented information and use it as a reference for determining the next action. The input is the answer data from the server, and the output is the legal information displayed to the user.

[0281] (Application Example 1)

[0282] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0283] Providing legal consultation services in a more efficient and convenient form is an important issue in modern society. In the conventional method, legal terms are difficult to understand and inaccessible to users without specialized knowledge. In addition, consulting an expert directly is time-consuming and costly, making it difficult for many people to use. Furthermore, legal consultation systems that utilize voice input are underdeveloped, and a mechanism is needed to obtain appropriate and prompt legal answers based on the user's voice.

[0284] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0285] In this invention, the server includes means for converting the user's voice input into text data by voice recognition technology, means for analyzing the text data by natural language processing technology to identify legal-related keywords and context, and means for querying the statute database and past case database based on the analysis result to generate an answer to the legal consultation in voice. As a result, legal information can be quickly obtained using voice, and it is possible to receive legal consultation in a form that is easy for the user to understand.

[0286] "Voice input" is the information provided by the user through voice for legal consultation.

[0287] "Speech recognition technology" is a technology that converts voice signals from a user into text format.

[0288] "Text data" refers to string data converted through speech recognition technology.

[0289] "Natural language processing technology" is a technique used to analyze text data and identify legal keywords and contexts.

[0290] "Legal keywords" are words or phrases that have significant meaning in legal documents or legal consultations.

[0291] "Context" refers to the surrounding words and sentences that determine the meaning of a keyword in text data.

[0292] A "legal database" is a system that stores and maintains laws and legal documents in a searchable format.

[0293] A "past case database" is a system that accumulates and manages cases that have been previously handled legally, allowing them to be referenced for similar legal issues.

[0294] "Speech synthesis technology" is a technology that converts text data of legal consultations into speech and uses it to respond to users.

[0295] "Legal advice answers" refer to advice or information generated based on a user's legal-related question.

[0296] A "user device" is an electronic device used by a user to input legal consultations and output responses.

[0297] This invention provides a system that efficiently delivers legal advice to users using voice, by combining speech recognition technology and natural language processing technology. This system is configured to operate appropriately at each stage of voice input acquisition, analysis, response generation, and response delivery. The hardware and software used, and their operation, are described below.

[0298] First, the user inputs a legal question via voice from their device through a specific operation. This voice data is converted into text data using software that performs speech recognition technology. Google Cloud Speech-to-Text is used here. This converted text data is then sent to a server.

[0299] The server analyzes the received text data using a natural language processing engine. Here, SpaCy is used to identify legal keywords and context from within the text. Based on the analysis results, the server accesses legal databases and past case databases via SQLite to extract relevant legal information.

[0300] Next, based on the extracted legal information, speech synthesis technology is used to generate legal advice answers for the user. Google Text-to-Speech is used for this process, and the generated audio data is sent to the user's device. This device provides the generated audio to the user, allowing the user to receive legal advice answers in a manner similar to that of a human expert.

[0301] For example, if a user asks a question related to divorce proceedings via voice, the terminal can convert the voice into text, and the server can analyze it to generate advice such as, "Property division should be based on an agreement between the spouses and should be divided considering the degree to which each party contributed to the creation and maintenance of the assets." An example of the prompt text in this case is as follows:

[0302] Example of a prompt:

[0303] "I want to consult about property division in divorce"

[0304] In this way, users can receive legal consultations in an efficient and easy-to-understand manner.

[0305] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0306] Step 1:

[0307] The user inputs a legal consultation question into the user terminal in voice. The terminal converts this voice into text data using Google Cloud Speech-to-Text. Through this conversion, an output in text format is obtained from an input in the form of a voice signal.

[0308] Step 2:

[0309] The terminal sends the converted text data to the server. The server receives this text data and performs analysis using natural language processing technology. Specifically, SpaCy is used to identify legal-related keywords and context from the input text. As a result, an output in the form of a keyword list is generated from an input of text data.

[0310] Step 3:

[0311] The server uses the identified keywords to query the statute database and the past case database using SQLite. Using the keyword list as input, relevant legal information is extracted. As a result, an output is obtained in the form of response materials using the information in the database.

[0312] Step 4:

[0313] The server uses natural language generation technology to prepare user-friendly legal advice answers based on extracted legal information. Google Text-to-Speech is used to convert the text-based answers into audio. In this process, audio data is generated from the input answer materials.

[0314] Step 5:

[0315] The server sends the generated audio data to the user's terminal. The terminal plays the audio data and provides the user with answers to their legal questions. The user receives input in the form of audio data and can receive legal advice by listening to the output.

[0316] This series of processes enables efficient legal consultations utilizing voice input.

[0317] 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.

[0318] This invention aims to improve the method of responding to users' legal consultations and provides an advanced information processing system incorporating an emotion engine. Specific embodiments are shown below.

[0319] First, the user enters their legal consultation details or questions into the device using natural language. The information entered by the user is sent from the device to the server. The server receives this data and first uses an emotion engine to analyze the user's emotions from the input text. Based on keywords and sentence structure in the text, the emotion engine identifies the emotions the user is likely feeling (e.g., anxiety, anger, relief).

[0320] After recognizing emotions, the server uses natural language processing technology to analyze the input information and identify legal keywords and context. Based on this analysis, the server queries legal databases and past case databases. The databases are linked to legal texts and case law databases, and relevant materials are referenced to extract the necessary legal information.

[0321] Next, the server uses natural language generation technology to generate a response for the user based on the extracted legal information. During this generation process, the tone and content of the response are adjusted according to the recognized emotions of the user. For example, if the user is feeling anxious, the response addresses this by using reassuring language and clearly outlining the steps to take. Furthermore, additional support information and words of comfort may be added to address the user's emotions.

[0322] The generated responses are sent from the server to the user's terminal and displayed in a user-friendly interface. This allows users to receive legal advice easily and with peace of mind.

[0323] As a concrete example, suppose a user seeks legal advice regarding a workplace problem. From the entered text, the emotion engine identifies signs of strong anxiety and stress in the user. The server takes this emotional information into consideration and provides advice on appropriate legal procedures, while also adding reassuring messages such as, "Please rest assured. You are fully protected by the law."

[0324] This system aims to comprehensively improve the accuracy of legal consultations and the user experience, thereby providing a better service.

[0325] The following describes the processing flow.

[0326] Step 1:

[0327] The user enters their legal consultation question into the terminal in natural language. For example, they might enter, "I want to know about the legal response to a workplace dispute." The terminal converts this input data into the appropriate format and sends it to the server.

[0328] Step 2:

[0329] The server receives data sent from the terminal. The received data is first sent to the emotion engine, which analyzes the user's emotions from the input text. For example, it identifies the level of anxiety or stress the user is feeling from the tone of voice and keywords in the text.

[0330] Step 3:

[0331] The server analyzes the data using natural language processing techniques, taking into account the emotions identified by the emotion engine. It extracts legal keywords and context, and uses this to understand the user's consultation content.

[0332] Step 4:

[0333] The server queries legal databases and past case databases based on the analyzed content. This extracts necessary legal information from relevant legal provisions, precedents, and past consultation cases. The server also works in conjunction with the complete collection of Japanese laws and case law databases to obtain accurate data.

[0334] Step 5:

[0335] The server generates responses using natural language generation technology based on extracted legal information, adjusting the content of the responses according to the perceived emotions of the user. To alleviate anxiety and stress, it can add reassuring expressions and specific action steps to the responses.

[0336] Step 6:

[0337] The server sends the generated response to the user's device. The transmitted data is displayed on the device in a format that is easy for the user to understand.

[0338] Step 7:

[0339] The device presents the user with the answer, allowing the user to take appropriate legal action based on that information. The user can then consider the next steps with a sense of security.

[0340] (Example 2)

[0341] 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".

[0342] Traditional legal consultation systems suffered from problems such as a lack of emotional consideration in the legal advice provided to users, and the use of complex and difficult-to-understand legal terminology. This led to users feeling anxious and being unable to fully utilize the information provided. Furthermore, insufficient integration between legal databases and past case databases posed a risk of reduced information accuracy.

[0343] 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.

[0344] In this invention, the server includes means for receiving legal input data from a user terminal, means for analyzing the input data using natural language processing technology to identify relevant terms and contexts, and means for adjusting the tone of advice based on the analyzed emotional elements. This enables the provision of emotionally sensitive and easy-to-understand legal advice, allowing users to use the system with confidence.

[0345] A "user terminal" is an electronic device that users directly operate to provide legal-related input data.

[0346] "Input data" refers to information provided by the user for legal consultation, and is typically text data expressed in natural language.

[0347] "Natural language processing technology" is a technology that enables computers to understand and appropriately analyze human language.

[0348] "Relevant terms and context" refers to words and phrases that are considered important in legal consultations, as well as the background situation and meaning behind them.

[0349] A "knowledge base" is a collection of data, including legal information and case precedents, that is used to provide appropriate legal advice.

[0350] "Emotional elements" refer to the emotional characteristics that users express in their input data, and include emotional states such as anxiety and reassurance.

[0351] "Legal advice" refers to solutions and guidelines provided to users in response to their legal inquiries, and is information generated to help users understand the subject.

[0352] The "tone of advice" refers to the way legal advice is expressed and the tone of voice, which is adjusted according to the user's emotions.

[0353] This system efficiently and emotionally supports users in seeking legal advice. The user begins by entering their legal consultation or question in natural language into their terminal. The user's terminal then sends the input data to a server. This transmission process typically utilizes the internet, and encryption technology is used to ensure secure data transmission.

[0354] The server uses natural language processing techniques to analyze the received input data. This technique identifies important legal terms and contexts. Morphological and contextual analysis algorithms are typically used for the analysis. Next, the server consults a knowledge base to extract legal information relevant to the input data. The knowledge base includes comprehensive legal codes and case law, and this information forms the basis for legal advice to the user.

[0355] Furthermore, the server also takes emotional factors into account. Using an emotion engine, it analyzes and identifies the emotions expressed by the user. Emotions such as anxiety, anger, and relief are extracted from the data, and the tone of the legal advice provided is adjusted accordingly.

[0356] As a concrete example, consider a case where a user enters, "I need advice regarding sexual harassment at work. I'm feeling anxious." The server analyzes this input, collecting legally relevant information while simultaneously recognizing the user's anxiety. Based on this, it generates advice in a tone such as, "Your rights are protected by law. Please rest assured," and sends it to the user's device.

[0357] This system uses a generative AI model to provide users with a safe and secure environment for legal consultations. Examples of prompts include, "I want legal advice regarding a workplace problem. What procedures should I follow?" In this way, users can receive support to address legal issues quickly and effectively.

[0358] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0359] Step 1:

[0360] The user inputs legal advice or questions into the terminal using natural language. The input data from the user is in text format, and the terminal receives this data and prepares to send it to the server. This step forms the basis for information gathering by the user.

[0361] Step 2:

[0362] The terminal sends input data received from the user to the server. The transmitted data is securely encrypted and delivered to the server via the internet connection. A special communication protocol is used during this process to maintain data integrity.

[0363] Step 3:

[0364] The server receives input data sent from the terminal and begins analysis using natural language processing techniques. The text data received as input is broken down by morphological analysis, and legal terms and related keywords are extracted. The analyzed information is then used for querying in the next step.

[0365] Step 4:

[0366] The server searches a knowledge base based on the analyzed keywords and contextual information. This knowledge base includes legal codes and case law data, serving as a foundation for querying relevant legal information. As output, legal information related to the user's inquiry is extracted and proceeds to the next generation process.

[0367] Step 5:

[0368] The server uses an emotion engine to analyze the user's emotional elements from the input data. Here, it identifies the user's emotions from the linguistic structure and vocabulary within the text, extracting emotional characteristics such as anxiety and reassurance. As output, this emotional information is used in the advice generation process.

[0369] Step 6:

[0370] The server generates legal advice using natural language generation technology, based on pre-extracted legal and emotional information. During this generation process, it adjusts the tone according to the user's emotions while constructing appropriate advice. The output is legal advice presented in a format that is easy for the user to understand.

[0371] Step 7:

[0372] The generated legal advice is sent from the server to the user's terminal. The user can receive this advice on their terminal and use it to assist in their legal consultation. The display interface is designed to make the advice easy for the user to read.

[0373] (Application Example 2)

[0374] 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."

[0375] When users seek legal advice, it is essential to provide appropriate legal advice based solely on the content of their inquiry. However, responses that disregard the user's emotional state can hinder the user experience. Traditional legal consultation systems focus on providing legal information but lack consideration for the user's emotional needs. Therefore, it is necessary to enhance user confidence and trust by appropriately adjusting legal consultation responses to the user's emotions.

[0376] 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.

[0377] In this invention, the server includes means for receiving legal-related input information from the user, means for analyzing the input information using natural language processing technology to identify legal-related keywords and context, and sentiment analysis technology for analyzing the user's emotions from the input information. This makes it possible to provide consistent legal consultation that takes into account not only the user's legal needs but also their emotional state.

[0378] A "user terminal" is a computer device used by users to input the details of their legal consultation and communicate with the server.

[0379] "Natural language processing technology" is a technique for converting text data into a form that computers can understand and then analyzing it.

[0380] "Legal keywords and context" refers to important legal terms and their meanings found within the input information.

[0381] "Emotion analysis technology" is a technology that identifies and analyzes emotions from text input by users.

[0382] A "legal database" is a collection of electronic data containing legal information such as legal codes and precedents.

[0383] "Natural language generation technology" is a technology that generates sentences that are natural and easy for humans to understand, based on information that a computer has understood.

[0384] "Legal consultation answers" refer to solutions and advice provided to users regarding their legal questions and problems.

[0385] "User-appropriate tone" refers to a tone and expression that is appropriate to the user's emotions and situation.

[0386] This invention describes embodiments for carrying out this invention. This system is configured with a server at its core that interacts with a user terminal for legal consultation. When a user inputs legal consultation information into the user terminal, that information is sent to the server. The server first analyzes the input information using natural language processing technology to identify legal-related keywords and context. For example, a computing device running an NLP library is used for this purpose.

[0387] Next, the user's emotions are analyzed using emotion analysis technology. This analysis utilizes emotion analysis engines (e.g., IBM Watson, Google Cloud Natural Language API) to extract emotions from the input text. Once emotions are identified, legal databases and past case databases are queried based on the analysis results to extract relevant legal information. This involves using database software that includes legal codes and case law data.

[0388] Based on extracted legal information and sentiment analysis results, natural language generation technology is used to generate legal advice responses in a tone appropriate to the user. The generated responses are sent to the user's terminal and displayed. A natural language generation engine (e.g., OpenAI's GPT series) is used in this process.

[0389] As a concrete example, consider a case where a user enters a legal consultation request stating, "I am worried about a problem at work." The system senses this anxiety and generates appropriate, emotionally responsive advice such as, "The problem is protected by law, so please rest assured. Here's how you should proceed next." In this way, the system considers the user's emotions during the legal consultation process, enabling it to provide more humane and reliable responses.

[0390] An example of a prompt for the generating AI model is as follows: "The user is expressing concern about noise problems with their neighbor. Please generate a response that provides reassurance while also outlining legal solutions."

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The user inputs the content of their legal consultation into their terminal using natural language. The entered text information is sent directly to the server; therefore, the primary input is the legal consultation text. The output is the text sent to the server.

[0394] Step 2:

[0395] The server analyzes the received text information using natural language processing (NLP) techniques. Specifically, it uses an NLP library to extract legal keywords and context. This process outputs specific terms related to the legal context.

[0396] Step 3:

[0397] The server analyzes the user's emotions using emotion analysis technology based on the parsed text information. Specifically, it uses an emotion analysis engine to identify emotions such as "anxiety," "relief," and "anger." The output of this process is data indicating the user's emotions.

[0398] Step 4:

[0399] The server queries legal databases and past case databases using legal keywords and sentiment data. It extracts appropriate legal information from the databases and outputs the relevant information.

[0400] Step 5:

[0401] The server uses extracted legal information and sentiment data to generate legal advice responses for the user using natural language generation technology. This process utilizes a generative AI model to create output that corresponds to the prompt text. The generated responses have a tone that matches the user's emotions.

[0402] Step 6:

[0403] The server sends the generated response to the user's terminal. The output response is presented to the user through the user interface, allowing the user to visually confirm it.

[0404] 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.

[0405] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0406] 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.

[0407] [Third Embodiment]

[0408] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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".

[0420] This invention is an information processing system for providing legal consultations efficiently and at a low cost. Specific embodiments are shown below.

[0421] The user begins by entering their legal questions or concerns into their device. The entered data is sent from the device to the server. The server uses natural language processing techniques to analyze this received data. This analysis identifies legal keywords and context. This step lays the foundation for determining which legal field (e.g., contracts, divorce, inheritance, etc.) the user's question relates to.

[0422] Next, the server queries legal databases and past case databases based on the identified keywords. This extracts information from relevant legal provisions, precedents, and similar past legal consultation cases. The server also connects with legal codes and case law databases to obtain the most accurate and comprehensive legal information possible.

[0423] Next, the server uses natural language generation technology to generate easy-to-understand legal advice answers based on the extracted legal information. The generated answers are designed to avoid technical jargon as much as possible and are presented in a way that is easy for the average user to understand. For example, it can explain the specific steps involved in inheritance procedures, such as "checking the will" and "creating an inheritance division agreement."

[0424] The generated response is sent from the server to the user's device. The device receives this response and displays it in an easy-to-understand interface. This allows the user to receive quick legal advice and smoothly decide on the next steps.

[0425] As a concrete example of this system, consider a case where a user seeks advice regarding divorce procedures. The user inputs "I want to know how to calculate property division in the event of divorce" through their terminal. The server analyzes this information, extracts relevant legal information, and generates advice such as "Property division should be decided through discussions between the spouses, and is generally divided based on the degree to which each person contributed to the formation and maintenance of the assets," which is then provided to the user.

[0426] As described above, the present invention provides a means for users to receive simple and prompt legal consultation, and is a system that makes legal support more accessible.

[0427] The following describes the processing flow.

[0428] Step 1:

[0429] Users input legal questions and inquiries into the terminal. For example, they might write specific details such as "How should I deal with deficiencies in a contract?" in the form. The terminal converts the entered data into the appropriate format and sends it to the server.

[0430] Step 2:

[0431] The server receives data sent from the terminal. It passes the received data to a natural language processing module, which then begins analysis. During this process, keywords and important contextual elements within the text are identified, and it is determined which legal field they relate to.

[0432] Step 3:

[0433] The server searches its internal legal database and past case database based on keywords identified through analysis. It refers to relevant legal provisions, precedents, and similar past consultations to extract important information. In doing so, it utilizes legal texts and case law databases to gather as much information as possible.

[0434] Step 4:

[0435] The server uses natural language generation technology to create user-friendly answers based on the collected legal information. The answers avoid legal jargon as much as possible and are written in language that is easy for general users to understand. For example, it might generate advice such as, "If there are deficiencies in the contract, it is advisable to create a revised agreement after discussions with the other party."

[0436] Step 5:

[0437] The server sends the generated response to the user's device. The transmitted data is formatted in a user-readable format by the device's interface.

[0438] Step 6:

[0439] The device notifies the user that the answer has been displayed and provides clear information for the user to take the necessary legal action. At this stage, the user can determine the next steps based on the consultation and take action.

[0440] (Example 1)

[0441] 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."

[0442] When seeking legal advice, users often face challenges such as the complexity of legal terminology and the difficulty of obtaining information quickly. As a result, consulting a legal professional can be time-consuming and expensive. Therefore, there is a need to provide a means for users to access legal advice easily and quickly.

[0443] 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.

[0444] In this invention, the server includes means for acquiring legal information from a user device, means for analyzing the information using language processing technology to identify legal indicators and background information, and means for referencing a legal information base and a past case information base based on the analysis results to retrieve relevant legal information. This makes it possible for users to obtain necessary legal information simply and efficiently without having to understand complex technical terms.

[0445] A "user device" is a terminal device used by a user to send and receive input information.

[0446] "Means of acquiring information" refers to the processes and technologies used by a server to receive legal information transmitted from a user device.

[0447] "Language processing technology" refers to techniques for analyzing natural language text and extracting meaning and keywords from it.

[0448] "Legal indicators and background" refers to key legal terms identified from user input information and the context behind them.

[0449] A "legal information base" is a database that contains official legal information such as legal provisions and precedents.

[0450] A "past case information base" is a database containing a collection of similar legal consultations and precedents from the past.

[0451] "Means of extracting information" refers to the process or technology of searching for and extracting relevant information from legal information databases and past case information databases based on specified conditions.

[0452] This invention is an information processing system that enables users to receive legal advice easily and quickly. A specific embodiment thereof is described below.

[0453] Users input legal questions and inquiries in text format using devices such as smartphones and personal computers. This input data is transmitted from the device to the server via a secure communication protocol (e.g., HTTPS).

[0454] The server uses state-of-the-art natural language processing techniques to analyze the received text data. Specifically, it employs language models such as BERT and generative AI models (e.g., GPT) to extract legal keywords and contextual information from the user's questions. This allows the server to identify which legal field the question relates to.

[0455] Next, the server references a legal information database and a past case information database based on the specified legal field. This database contains legal articles, precedents, and past consultation cases, and the necessary information can be searched and extracted using methods such as SQL queries.

[0456] Based on the extracted legal information, the server uses a generative AI model to create answers for the user. The generated text is simplified, avoiding technical jargon, and presented in a format easily understood by the average user. For example, if a user enters "Tell me about inheritance procedures," the server will generate a response such as "A detailed guide on how to check a will and how to create an inheritance division agreement."

[0457] Finally, the server resends the generated response to the user's device. The device receives this response and displays it visually in an easy-to-understand format on the user interface. This allows the user to obtain quick and detailed legal advice and appropriately decide on the next steps based on their situation and requirements.

[0458] A concrete example of a prompt message would be something like, "I want to create a contract, what should I be careful about?"

[0459] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0460] Step 1:

[0461] The user uses a terminal to input legal questions. An example input might be, "How is property division calculated during divorce?" This text data is entered on the terminal and sent to the server via the internet. The output from the terminal is the text data entered by the user.

[0462] Step 2:

[0463] The server receives text data sent from the terminal. The received data is raw natural language information. Based on this input data, the server begins analysis using natural language processing techniques. The input is legal text from the terminal, and the output is data with identified legal keywords and context. Specifically, the server extracts the relationship between keywords such as "divorce" and "property division" and their background from the text.

[0464] Step 3:

[0465] The server uses the analyzed data to query the legal information base and the historical case information base. In this step, information in the identified legal field is searched, and relevant legal articles and precedents are retrieved. The input is the analyzed keyword data, and the output is a set of relevant legal information. For example, legal provisions related to property division in divorce cases may be extracted.

[0466] Step 4:

[0467] The server uses a generative AI model to generate user-friendly answers based on the legal information it retrieves through searches. The input is extracted legal information, and the output is a user-friendly answer. For example, it might generate a specific answer such as, "Property division usually recommends dividing assets accumulated jointly by a married couple based on certain criteria."

[0468] Step 5:

[0469] The server sends the generated response to the user's terminal. The server transfers the generated text to the terminal via the internet. The input is the generated response text, and the output is data ready for display on the terminal.

[0470] Step 6:

[0471] The terminal receives legal responses sent from the server and displays them on the user interface. Users can review the visually represented information and use it as a reference to decide on their next course of action. The input is the response data from the server, and the output is the legal information displayed to the user.

[0472] (Application Example 1)

[0473] 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."

[0474] Providing legal consultation services in a more efficient and convenient manner is a crucial challenge in modern society. Traditional methods often involve complex legal terminology, making them difficult for users without specialized knowledge to access. Furthermore, direct consultations with experts are time-consuming and costly, making them inaccessible to many. Additionally, legal consultation systems utilizing voice input are underdeveloped, highlighting the need for a system that can provide appropriate and prompt legal answers based on user voice input.

[0475] 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.

[0476] In this invention, the server includes means for converting user voice input into text data using speech recognition technology, means for analyzing the text data using natural language processing technology to identify legal keywords and context, and means for querying a legal database and a past case database based on the analysis results to generate a legal consultation response in voice. This makes it possible to quickly obtain legal information using voice and to receive legal consultation in a format that is easy for the user to understand.

[0477] "Voice input" refers to information provided by users via voice for legal consultation.

[0478] "Speech recognition technology" is a technology that converts voice signals from a user into text format.

[0479] "Text data" refers to string data converted through speech recognition technology.

[0480] "Natural language processing technology" is a technique used to analyze text data and identify legal keywords and contexts.

[0481] "Legal keywords" are words or phrases that have significant meaning in legal documents or legal consultations.

[0482] "Context" refers to the surrounding words and sentences that determine the meaning of a keyword in text data.

[0483] A "legal database" is a system that stores and maintains laws and legal documents in a searchable format.

[0484] A "past case database" is a system that accumulates and manages cases that have been previously handled legally, allowing them to be referenced for similar legal issues.

[0485] "Speech synthesis technology" is a technology that converts text data of legal consultations into speech and uses it to respond to users.

[0486] "Legal advice answers" refer to advice or information generated based on a user's legal-related question.

[0487] A "user device" is an electronic device used by a user to input legal consultations and output responses.

[0488] This invention provides a system that efficiently delivers legal advice to users using voice, by combining speech recognition technology and natural language processing technology. This system is configured to operate appropriately at each stage of voice input acquisition, analysis, response generation, and response delivery. The hardware and software used, and their operation, are described below.

[0489] First, the user inputs a legal question via voice from their device through a specific operation. This voice data is converted into text data using software that performs speech recognition technology. Google Cloud Speech-to-Text is used here. This converted text data is then sent to a server.

[0490] The server analyzes the received text data using a natural language processing engine. Here, SpaCy is used to identify legal keywords and context from within the text. Based on the analysis results, the server accesses legal databases and past case databases via SQLite to extract relevant legal information.

[0491] Next, based on the extracted legal information, speech synthesis technology is used to generate legal advice answers for the user. Google Text-to-Speech is used for this process, and the generated audio data is sent to the user's device. This device provides the generated audio to the user, allowing the user to receive legal advice answers in a manner similar to that of a human expert.

[0492] For example, if a user asks a question related to divorce proceedings via voice, the terminal can convert the voice into text, and the server can analyze it to generate advice such as, "Property division should be based on an agreement between the spouses and should be divided considering the degree to which each party contributed to the creation and maintenance of the assets." An example of the prompt text in this case is as follows:

[0493] Example of a prompt:

[0494] "I would like to consult about property division in a divorce."

[0495] In this way, users can receive legal advice in an efficient and easy-to-understand manner.

[0496] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0497] Step 1:

[0498] The user inputs their legal consultation question via voice into their device. The device then converts this voice into text data using Google Cloud Speech-to-Text. This conversion process yields text output from an input in the form of an audio signal.

[0499] Step 2:

[0500] The terminal sends the converted text data to the server. The server receives this text data and performs analysis using natural language processing techniques. Specifically, it uses SpaCy to identify legal-related keywords and context from the input text. This generates a keyword list as output from the text data input.

[0501] Step 3:

[0502] The server uses specified keywords to query legal databases and past case databases using SQLite. A keyword list is used as input to extract relevant legal information. This results in output in the form of response materials based on the database information.

[0503] Step 4:

[0504] The server uses natural language generation technology to prepare user-friendly legal advice answers based on extracted legal information. Google Text-to-Speech is used to convert the text-based answers into audio. In this process, audio data is generated from the input answer materials.

[0505] Step 5:

[0506] The server sends the generated audio data to the user's terminal. The terminal plays the audio data and provides the user with answers to their legal questions. The user receives input in the form of audio data and can receive legal advice by listening to the output.

[0507] This series of processes enables efficient legal consultations utilizing voice input.

[0508] 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.

[0509] This invention aims to improve the method of responding to users' legal consultations and provides an advanced information processing system incorporating an emotion engine. Specific embodiments are shown below.

[0510] First, the user enters their legal consultation details or questions into the device using natural language. The information entered by the user is sent from the device to the server. The server receives this data and first uses an emotion engine to analyze the user's emotions from the input text. Based on keywords and sentence structure in the text, the emotion engine identifies the emotions the user is likely feeling (e.g., anxiety, anger, relief).

[0511] After recognizing emotions, the server uses natural language processing technology to analyze the input information and identify legal keywords and context. Based on this analysis, the server queries legal databases and past case databases. The databases are linked to legal texts and case law databases, and relevant materials are referenced to extract the necessary legal information.

[0512] Next, the server uses natural language generation technology to generate a response for the user based on the extracted legal information. During this generation process, the tone and content of the response are adjusted according to the recognized emotions of the user. For example, if the user is feeling anxious, the response addresses this by using reassuring language and clearly outlining the steps to take. Furthermore, additional support information and words of comfort may be added to address the user's emotions.

[0513] The generated responses are sent from the server to the user's terminal and displayed in a user-friendly interface. This allows users to receive legal advice easily and with peace of mind.

[0514] As a concrete example, suppose a user seeks legal advice regarding a workplace problem. From the entered text, the emotion engine identifies signs of strong anxiety and stress in the user. The server takes this emotional information into consideration and provides advice on appropriate legal procedures, while also adding reassuring messages such as, "Please rest assured. You are fully protected by the law."

[0515] This system aims to comprehensively improve the accuracy of legal consultations and the user experience, thereby providing a better service.

[0516] The following describes the processing flow.

[0517] Step 1:

[0518] The user enters their legal consultation question into the terminal in natural language. For example, they might enter, "I want to know about the legal response to a workplace dispute." The terminal converts this input data into the appropriate format and sends it to the server.

[0519] Step 2:

[0520] The server receives data sent from the terminal. The received data is first sent to the emotion engine, which analyzes the user's emotions from the input text. For example, it identifies the level of anxiety or stress the user is feeling from the tone of voice and keywords in the text.

[0521] Step 3:

[0522] The server analyzes the data using natural language processing techniques, taking into account the emotions identified by the emotion engine. It extracts legal keywords and context, and uses this to understand the user's consultation content.

[0523] Step 4:

[0524] The server queries legal databases and past case databases based on the analyzed content. This extracts necessary legal information from relevant legal provisions, precedents, and past consultation cases. The server also works in conjunction with the complete collection of Japanese laws and case law databases to obtain accurate data.

[0525] Step 5:

[0526] The server generates responses using natural language generation technology based on extracted legal information, adjusting the content of the responses according to the perceived emotions of the user. To alleviate anxiety and stress, it can add reassuring expressions and specific action steps to the responses.

[0527] Step 6:

[0528] The server sends the generated response to the user's device. The transmitted data is displayed on the device in a format that is easy for the user to understand.

[0529] Step 7:

[0530] The device presents the user with the answer, allowing the user to take appropriate legal action based on that information. The user can then consider the next steps with a sense of security.

[0531] (Example 2)

[0532] 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."

[0533] Traditional legal consultation systems suffered from problems such as a lack of emotional consideration in the legal advice provided to users, and the use of complex and difficult-to-understand legal terminology. This led to users feeling anxious and being unable to fully utilize the information provided. Furthermore, insufficient integration between legal databases and past case databases posed a risk of reduced information accuracy.

[0534] 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.

[0535] In this invention, the server includes means for receiving legal input data from a user terminal, means for analyzing the input data using natural language processing technology to identify relevant terms and contexts, and means for adjusting the tone of advice based on the analyzed emotional elements. This enables the provision of emotionally sensitive and easy-to-understand legal advice, allowing users to use the system with confidence.

[0536] A "user terminal" is an electronic device that users directly operate to provide legal-related input data.

[0537] "Input data" refers to information provided by the user for legal consultation, and is typically text data expressed in natural language.

[0538] "Natural language processing technology" is a technology that enables computers to understand and appropriately analyze human language.

[0539] "Relevant terms and context" refers to words and phrases that are considered important in legal consultations, as well as the background situation and meaning behind them.

[0540] A "knowledge base" is a collection of data, including legal information and case precedents, that is used to provide appropriate legal advice.

[0541] "Emotional elements" refer to the emotional characteristics that users express in their input data, and include emotional states such as anxiety and reassurance.

[0542] "Legal advice" refers to solutions and guidelines provided to users in response to their legal inquiries, and is information generated to help users understand the subject.

[0543] The "tone of advice" refers to the way legal advice is expressed and the tone of voice, which is adjusted according to the user's emotions.

[0544] This system efficiently and emotionally supports users in seeking legal advice. The user begins by entering their legal consultation or question in natural language into their terminal. The user's terminal then sends the input data to a server. This transmission process typically utilizes the internet, and encryption technology is used to ensure secure data transmission.

[0545] The server uses natural language processing techniques to analyze the received input data. This technique identifies important legal terms and contexts. Morphological and contextual analysis algorithms are typically used for the analysis. Next, the server consults a knowledge base to extract legal information relevant to the input data. The knowledge base includes comprehensive legal codes and case law, and this information forms the basis for legal advice to the user.

[0546] Furthermore, the server also takes emotional factors into account. Using an emotion engine, it analyzes and identifies the emotions expressed by the user. Emotions such as anxiety, anger, and relief are extracted from the data, and the tone of the legal advice provided is adjusted accordingly.

[0547] As a concrete example, consider a case where a user enters, "I need advice regarding sexual harassment at work. I'm feeling anxious." The server analyzes this input, collecting legally relevant information while simultaneously recognizing the user's anxiety. Based on this, it generates advice in a tone such as, "Your rights are protected by law. Please rest assured," and sends it to the user's device.

[0548] This system uses a generative AI model to provide users with a safe and secure environment for legal consultations. Examples of prompts include, "I want legal advice regarding a workplace problem. What procedures should I follow?" In this way, users can receive support to address legal issues quickly and effectively.

[0549] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0550] Step 1:

[0551] The user inputs legal advice or questions into the terminal using natural language. The input data from the user is in text format, and the terminal receives this data and prepares to send it to the server. This step forms the basis for information gathering by the user.

[0552] Step 2:

[0553] The terminal sends input data received from the user to the server. The transmitted data is securely encrypted and delivered to the server via the internet connection. A special communication protocol is used during this process to maintain data integrity.

[0554] Step 3:

[0555] The server receives input data sent from the terminal and begins analysis using natural language processing techniques. The text data received as input is broken down by morphological analysis, and legal terms and related keywords are extracted. The analyzed information is then used for querying in the next step.

[0556] Step 4:

[0557] The server searches a knowledge base based on the analyzed keywords and contextual information. This knowledge base includes legal codes and case law data, serving as a foundation for querying relevant legal information. As output, legal information related to the user's inquiry is extracted and proceeds to the next generation process.

[0558] Step 5:

[0559] The server uses an emotion engine to analyze the user's emotional elements from the input data. Here, it identifies the user's emotions from the linguistic structure and vocabulary within the text, extracting emotional characteristics such as anxiety and reassurance. As output, this emotional information is used in the advice generation process.

[0560] Step 6:

[0561] The server generates legal advice using natural language generation technology, based on pre-extracted legal and emotional information. During this generation process, it adjusts the tone according to the user's emotions while constructing appropriate advice. The output is legal advice presented in a format that is easy for the user to understand.

[0562] Step 7:

[0563] The generated legal advice is sent from the server to the user's terminal. The user can receive this advice on their terminal and use it to assist in their legal consultation. The display interface is designed to make the advice easy for the user to read.

[0564] (Application Example 2)

[0565] 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."

[0566] When users seek legal advice, it is essential to provide appropriate legal advice based solely on the content of their inquiry. However, responses that disregard the user's emotional state can hinder the user experience. Traditional legal consultation systems focus on providing legal information but lack consideration for the user's emotional needs. Therefore, it is necessary to enhance user confidence and trust by appropriately adjusting legal consultation responses to the user's emotions.

[0567] 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.

[0568] In this invention, the server includes means for receiving legal-related input information from the user, means for analyzing the input information using natural language processing technology to identify legal-related keywords and context, and sentiment analysis technology for analyzing the user's emotions from the input information. This makes it possible to provide consistent legal consultation that takes into account not only the user's legal needs but also their emotional state.

[0569] A "user terminal" is a computer device used by users to input the details of their legal consultation and communicate with the server.

[0570] "Natural language processing technology" is a technique for converting text data into a form that computers can understand and then analyzing it.

[0571] "Legal keywords and context" refers to important legal terms and their meanings found within the input information.

[0572] "Emotion analysis technology" is a technology that identifies and analyzes emotions from text input by users.

[0573] A "legal database" is a collection of electronic data containing legal information such as legal codes and precedents.

[0574] "Natural language generation technology" is a technology that generates sentences that are natural and easy for humans to understand, based on information that a computer has understood.

[0575] "Legal consultation answers" refer to solutions and advice provided to users regarding their legal questions and problems.

[0576] "User-appropriate tone" refers to a tone and expression that is appropriate to the user's emotions and situation.

[0577] This invention describes embodiments for carrying out this invention. This system is configured with a server at its core that interacts with a user terminal for legal consultation. When a user inputs legal consultation information into the user terminal, that information is sent to the server. The server first analyzes the input information using natural language processing technology to identify legal-related keywords and context. For example, a computing device running an NLP library is used for this purpose.

[0578] Next, the user's emotions are analyzed using emotion analysis technology. This analysis utilizes emotion analysis engines (e.g., IBM Watson, Google Cloud Natural Language API) to extract emotions from the input text. Once emotions are identified, legal databases and past case databases are queried based on the analysis results to extract relevant legal information. This involves using database software that includes legal codes and case law data.

[0579] Based on extracted legal information and sentiment analysis results, natural language generation technology is used to generate legal advice responses in a tone appropriate to the user. The generated responses are sent to the user's terminal and displayed. A natural language generation engine (e.g., OpenAI's GPT series) is used in this process.

[0580] As a concrete example, consider a case where a user enters a legal consultation request stating, "I am worried about a problem at work." The system senses this anxiety and generates appropriate, emotionally responsive advice such as, "The problem is protected by law, so please rest assured. Here's how you should proceed next." In this way, the system considers the user's emotions during the legal consultation process, enabling it to provide more humane and reliable responses.

[0581] An example of a prompt for the generating AI model is as follows: "The user is expressing concern about noise problems with their neighbor. Please generate a response that provides reassurance while also outlining legal solutions."

[0582] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0583] Step 1:

[0584] The user inputs the content of their legal consultation into their terminal using natural language. The entered text information is sent directly to the server; therefore, the primary input is the legal consultation text. The output is the text sent to the server.

[0585] Step 2:

[0586] The server analyzes the received text information using natural language processing (NLP) techniques. Specifically, it uses an NLP library to extract legal keywords and context. This process outputs specific terms related to the legal context.

[0587] Step 3:

[0588] The server analyzes the user's emotions using emotion analysis technology based on the parsed text information. Specifically, it uses an emotion analysis engine to identify emotions such as "anxiety," "relief," and "anger." The output of this process is data indicating the user's emotions.

[0589] Step 4:

[0590] The server queries legal databases and past case databases using legal keywords and sentiment data. It extracts appropriate legal information from the databases and outputs the relevant information.

[0591] Step 5:

[0592] The server uses extracted legal information and sentiment data to generate legal advice responses for the user using natural language generation technology. This process utilizes a generative AI model to create output that corresponds to the prompt text. The generated responses have a tone that matches the user's emotions.

[0593] Step 6:

[0594] The server sends the generated response to the user's terminal. The output response is presented to the user through the user interface, allowing the user to visually confirm it.

[0595] 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.

[0596] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0597] 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.

[0598] [Fourth Embodiment]

[0599] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0600] 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.

[0601] 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).

[0602] 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.

[0603] 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.

[0604] 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).

[0605] 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.

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] 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".

[0612] This invention is an information processing system for providing legal consultations efficiently and at a low cost. Specific embodiments are shown below.

[0613] The user begins by entering their legal questions or concerns into their device. The entered data is sent from the device to the server. The server uses natural language processing techniques to analyze this received data. This analysis identifies legal keywords and context. This step lays the foundation for determining which legal field (e.g., contracts, divorce, inheritance, etc.) the user's question relates to.

[0614] Next, the server queries legal databases and past case databases based on the identified keywords. This extracts information from relevant legal provisions, precedents, and similar past legal consultation cases. The server also connects with legal codes and case law databases to obtain the most accurate and comprehensive legal information possible.

[0615] Next, the server uses natural language generation technology to generate easy-to-understand legal advice answers based on the extracted legal information. The generated answers are designed to avoid technical jargon as much as possible and are presented in a way that is easy for the average user to understand. For example, it can explain the specific steps involved in inheritance procedures, such as "checking the will" and "creating an inheritance division agreement."

[0616] The generated response is sent from the server to the user's device. The device receives this response and displays it in an easy-to-understand interface. This allows the user to receive quick legal advice and smoothly decide on the next steps.

[0617] As a concrete example of this system, consider a case where a user seeks advice regarding divorce procedures. The user inputs "I want to know how to calculate property division in the event of divorce" through their terminal. The server analyzes this information, extracts relevant legal information, and generates advice such as "Property division should be decided through discussions between the spouses, and is generally divided based on the degree to which each person contributed to the formation and maintenance of the assets," which is then provided to the user.

[0618] As described above, the present invention provides a means for users to receive simple and prompt legal consultation, and is a system that makes legal support more accessible.

[0619] The following describes the processing flow.

[0620] Step 1:

[0621] Users input legal questions and inquiries into the terminal. For example, they might write specific details such as "How should I deal with deficiencies in a contract?" in the form. The terminal converts the entered data into the appropriate format and sends it to the server.

[0622] Step 2:

[0623] The server receives data sent from the terminal. It passes the received data to a natural language processing module, which then begins analysis. During this process, keywords and important contextual elements within the text are identified, and it is determined which legal field they relate to.

[0624] Step 3:

[0625] The server searches its internal legal database and past case database based on keywords identified through analysis. It refers to relevant legal provisions, precedents, and similar past consultations to extract important information. In doing so, it utilizes legal texts and case law databases to gather as much information as possible.

[0626] Step 4:

[0627] The server uses natural language generation technology to create user-friendly answers based on the collected legal information. The answers avoid legal jargon as much as possible and are written in language that is easy for general users to understand. For example, it might generate advice such as, "If there are deficiencies in the contract, it is advisable to create a revised agreement after discussions with the other party."

[0628] Step 5:

[0629] The server sends the generated response to the user's device. The transmitted data is formatted in a user-readable format by the device's interface.

[0630] Step 6:

[0631] The device notifies the user that the answer has been displayed and provides clear information for the user to take the necessary legal action. At this stage, the user can determine the next steps based on the consultation and take action.

[0632] (Example 1)

[0633] 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".

[0634] When seeking legal advice, users often face challenges such as the complexity of legal terminology and the difficulty of obtaining information quickly. As a result, consulting a legal professional can be time-consuming and expensive. Therefore, there is a need to provide a means for users to access legal advice easily and quickly.

[0635] 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.

[0636] In this invention, the server includes means for acquiring legal information from a user device, means for analyzing the information using language processing technology to identify legal indicators and background information, and means for referencing a legal information base and a past case information base based on the analysis results to retrieve relevant legal information. This makes it possible for users to obtain necessary legal information simply and efficiently without having to understand complex technical terms.

[0637] A "user device" is a terminal device used by a user to send and receive input information.

[0638] "Means of acquiring information" refers to the processes and technologies used by a server to receive legal information transmitted from a user device.

[0639] "Language processing technology" refers to techniques for analyzing natural language text and extracting meaning and keywords from it.

[0640] "Legal indicators and background" refers to key legal terms identified from user input information and the context behind them.

[0641] A "legal information base" is a database that contains official legal information such as legal provisions and precedents.

[0642] A "past case information base" is a database containing a collection of similar legal consultations and precedents from the past.

[0643] "Means of extracting information" refers to the process or technology of searching for and extracting relevant information from legal information databases and past case information databases based on specified conditions.

[0644] This invention is an information processing system that enables users to receive legal advice easily and quickly. A specific embodiment thereof is described below.

[0645] Users input legal questions and inquiries in text format using devices such as smartphones and personal computers. This input data is transmitted from the device to the server via a secure communication protocol (e.g., HTTPS).

[0646] The server uses state-of-the-art natural language processing techniques to analyze the received text data. Specifically, it employs language models such as BERT and generative AI models (e.g., GPT) to extract legal keywords and contextual information from the user's questions. This allows the server to identify which legal field the question relates to.

[0647] Next, the server references a legal information database and a past case information database based on the specified legal field. This database contains legal articles, precedents, and past consultation cases, and the necessary information can be searched and extracted using methods such as SQL queries.

[0648] Based on the extracted legal information, the server uses a generative AI model to create answers for the user. The generated text is simplified, avoiding technical jargon, and presented in a format easily understood by the average user. For example, if a user enters "Tell me about inheritance procedures," the server will generate a response such as "A detailed guide on how to check a will and how to create an inheritance division agreement."

[0649] Finally, the server resends the generated response to the user's device. The device receives this response and displays it visually in an easy-to-understand format on the user interface. This allows the user to obtain quick and detailed legal advice and appropriately decide on the next steps based on their situation and requirements.

[0650] A concrete example of a prompt message would be something like, "I want to create a contract, what should I be careful about?"

[0651] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0652] Step 1:

[0653] The user uses a terminal to input legal questions. An example input might be, "How is property division calculated during divorce?" This text data is entered on the terminal and sent to the server via the internet. The output from the terminal is the text data entered by the user.

[0654] Step 2:

[0655] The server receives text data sent from the terminal. The received data is raw natural language information. Based on this input data, the server begins analysis using natural language processing techniques. The input is legal text from the terminal, and the output is data with identified legal keywords and context. Specifically, the server extracts the relationship between keywords such as "divorce" and "property division" and their background from the text.

[0656] Step 3:

[0657] The server uses the analyzed data to query the legal information base and the historical case information base. In this step, information in the identified legal field is searched, and relevant legal articles and precedents are retrieved. The input is the analyzed keyword data, and the output is a set of relevant legal information. For example, legal provisions related to property division in divorce cases may be extracted.

[0658] Step 4:

[0659] The server uses a generative AI model to generate user-friendly answers based on the legal information it retrieves through searches. The input is extracted legal information, and the output is a user-friendly answer. For example, it might generate a specific answer such as, "Property division usually recommends dividing assets accumulated jointly by a married couple based on certain criteria."

[0660] Step 5:

[0661] The server sends the generated response to the user's terminal. The server transfers the generated text to the terminal via the internet. The input is the generated response text, and the output is data ready for display on the terminal.

[0662] Step 6:

[0663] The terminal receives legal responses sent from the server and displays them on the user interface. Users can review the visually represented information and use it as a reference to decide on their next course of action. The input is the response data from the server, and the output is the legal information displayed to the user.

[0664] (Application Example 1)

[0665] 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".

[0666] Providing legal consultation services in a more efficient and convenient manner is a crucial challenge in modern society. Traditional methods often involve complex legal terminology, making them difficult for users without specialized knowledge to access. Furthermore, direct consultations with experts are time-consuming and costly, making them inaccessible to many. Additionally, legal consultation systems utilizing voice input are underdeveloped, highlighting the need for a system that can provide appropriate and prompt legal answers based on user voice input.

[0667] 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.

[0668] In this invention, the server includes means for converting user voice input into text data using speech recognition technology, means for analyzing the text data using natural language processing technology to identify legal keywords and context, and means for querying a legal database and a past case database based on the analysis results to generate a legal consultation response in voice. This makes it possible to quickly obtain legal information using voice and to receive legal consultation in a format that is easy for the user to understand.

[0669] "Voice input" refers to information provided by users via voice for legal consultation.

[0670] "Speech recognition technology" is a technology that converts voice signals from a user into text format.

[0671] "Text data" refers to string data converted through speech recognition technology.

[0672] "Natural language processing technology" is a technique used to analyze text data and identify legal keywords and contexts.

[0673] "Legal keywords" are words or phrases that have significant meaning in legal documents or legal consultations.

[0674] "Context" refers to the surrounding words and sentences that determine the meaning of a keyword in text data.

[0675] A "legal database" is a system that stores and maintains laws and legal documents in a searchable format.

[0676] A "past case database" is a system that accumulates and manages cases that have been previously handled legally, allowing them to be referenced for similar legal issues.

[0677] "Speech synthesis technology" is a technology that converts text data of legal consultations into speech and uses it to respond to users.

[0678] "Legal advice answers" refer to advice or information generated based on a user's legal-related question.

[0679] A "user device" is an electronic device used by a user to input legal consultations and output responses.

[0680] This invention provides a system that efficiently delivers legal advice to users using voice, by combining speech recognition technology and natural language processing technology. This system is configured to operate appropriately at each stage of voice input acquisition, analysis, response generation, and response delivery. The hardware and software used, and their operation, are described below.

[0681] First, the user inputs a legal question via voice from their device through a specific operation. This voice data is converted into text data using software that performs speech recognition technology. Google Cloud Speech-to-Text is used here. This converted text data is then sent to a server.

[0682] The server analyzes the received text data using a natural language processing engine. Here, SpaCy is used to identify legal keywords and context from within the text. Based on the analysis results, the server accesses legal databases and past case databases via SQLite to extract relevant legal information.

[0683] Next, based on the extracted legal information, speech synthesis technology is used to generate legal advice answers for the user. Google Text-to-Speech is used for this process, and the generated audio data is sent to the user's device. This device provides the generated audio to the user, allowing the user to receive legal advice answers in a manner similar to that of a human expert.

[0684] For example, if a user asks a question related to divorce proceedings via voice, the terminal can convert the voice into text, and the server can analyze it to generate advice such as, "Property division should be based on an agreement between the spouses and should be divided considering the degree to which each party contributed to the creation and maintenance of the assets." An example of the prompt text in this case is as follows:

[0685] Example of a prompt:

[0686] "I would like to consult about property division in a divorce."

[0687] In this way, users can receive legal advice in an efficient and easy-to-understand manner.

[0688] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0689] Step 1:

[0690] The user inputs their legal consultation question via voice into their device. The device then converts this voice into text data using Google Cloud Speech-to-Text. This conversion process yields text output from an input in the form of an audio signal.

[0691] Step 2:

[0692] The terminal sends the converted text data to the server. The server receives this text data and performs analysis using natural language processing techniques. Specifically, it uses SpaCy to identify legal-related keywords and context from the input text. This generates a keyword list as output from the text data input.

[0693] Step 3:

[0694] The server uses specified keywords to query legal databases and past case databases using SQLite. A keyword list is used as input to extract relevant legal information. This results in output in the form of response materials based on the database information.

[0695] Step 4:

[0696] The server uses natural language generation technology to prepare user-friendly legal advice answers based on extracted legal information. Google Text-to-Speech is used to convert the text-based answers into audio. In this process, audio data is generated from the input answer materials.

[0697] Step 5:

[0698] The server sends the generated audio data to the user's terminal. The terminal plays the audio data and provides the user with answers to their legal questions. The user receives input in the form of audio data and can receive legal advice by listening to the output.

[0699] This series of processes enables efficient legal consultations utilizing voice input.

[0700] 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.

[0701] This invention aims to improve the method of responding to users' legal consultations and provides an advanced information processing system incorporating an emotion engine. Specific embodiments are shown below.

[0702] First, the user enters their legal consultation details or questions into the device using natural language. The information entered by the user is sent from the device to the server. The server receives this data and first uses an emotion engine to analyze the user's emotions from the input text. Based on keywords and sentence structure in the text, the emotion engine identifies the emotions the user is likely feeling (e.g., anxiety, anger, relief).

[0703] After recognizing emotions, the server uses natural language processing technology to analyze the input information and identify legal keywords and context. Based on this analysis, the server queries legal databases and past case databases. The databases are linked to legal texts and case law databases, and relevant materials are referenced to extract the necessary legal information.

[0704] Next, the server uses natural language generation technology to generate a response for the user based on the extracted legal information. During this generation process, the tone and content of the response are adjusted according to the recognized emotions of the user. For example, if the user is feeling anxious, the response addresses this by using reassuring language and clearly outlining the steps to take. Furthermore, additional support information and words of comfort may be added to address the user's emotions.

[0705] The generated responses are sent from the server to the user's terminal and displayed in a user-friendly interface. This allows users to receive legal advice easily and with peace of mind.

[0706] As a concrete example, suppose a user seeks legal advice regarding a workplace problem. From the entered text, the emotion engine identifies signs of strong anxiety and stress in the user. The server takes this emotional information into consideration and provides advice on appropriate legal procedures, while also adding reassuring messages such as, "Please rest assured. You are fully protected by the law."

[0707] This system aims to comprehensively improve the accuracy of legal consultations and the user experience, thereby providing a better service.

[0708] The following describes the processing flow.

[0709] Step 1:

[0710] The user enters their legal consultation question into the terminal in natural language. For example, they might enter, "I want to know about the legal response to a workplace dispute." The terminal converts this input data into the appropriate format and sends it to the server.

[0711] Step 2:

[0712] The server receives data sent from the terminal. The received data is first sent to the emotion engine, which analyzes the user's emotions from the input text. For example, it identifies the level of anxiety or stress the user is feeling from the tone of voice and keywords in the text.

[0713] Step 3:

[0714] The server analyzes the data using natural language processing techniques, taking into account the emotions identified by the emotion engine. It extracts legal keywords and context, and uses this to understand the user's consultation content.

[0715] Step 4:

[0716] The server queries legal databases and past case databases based on the analyzed content. This extracts necessary legal information from relevant legal provisions, precedents, and past consultation cases. The server also works in conjunction with the complete collection of Japanese laws and case law databases to obtain accurate data.

[0717] Step 5:

[0718] The server generates responses using natural language generation technology based on extracted legal information, adjusting the content of the responses according to the perceived emotions of the user. To alleviate anxiety and stress, it can add reassuring expressions and specific action steps to the responses.

[0719] Step 6:

[0720] The server sends the generated response to the user's device. The transmitted data is displayed on the device in a format that is easy for the user to understand.

[0721] Step 7:

[0722] The device presents the user with the answer, allowing the user to take appropriate legal action based on that information. The user can then consider the next steps with a sense of security.

[0723] (Example 2)

[0724] 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".

[0725] Traditional legal consultation systems suffered from problems such as a lack of emotional consideration in the legal advice provided to users, and the use of complex and difficult-to-understand legal terminology. This led to users feeling anxious and being unable to fully utilize the information provided. Furthermore, insufficient integration between legal databases and past case databases posed a risk of reduced information accuracy.

[0726] 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.

[0727] In this invention, the server includes means for receiving legal input data from a user terminal, means for analyzing the input data using natural language processing technology to identify relevant terms and contexts, and means for adjusting the tone of advice based on the analyzed emotional elements. This enables the provision of emotionally sensitive and easy-to-understand legal advice, allowing users to use the system with confidence.

[0728] A "user terminal" is an electronic device that users directly operate to provide legal-related input data.

[0729] "Input data" refers to information provided by the user for legal consultation, and is typically text data expressed in natural language.

[0730] "Natural language processing technology" is a technology that enables computers to understand and appropriately analyze human language.

[0731] "Relevant terms and context" refers to words and phrases that are considered important in legal consultations, as well as the background situation and meaning behind them.

[0732] A "knowledge base" is a collection of data, including legal information and case precedents, that is used to provide appropriate legal advice.

[0733] "Emotional elements" refer to the emotional characteristics that users express in their input data, and include emotional states such as anxiety and reassurance.

[0734] "Legal advice" refers to solutions and guidelines provided to users in response to their legal inquiries, and is information generated to help users understand the subject.

[0735] The "tone of advice" refers to the way legal advice is expressed and the tone of voice, which is adjusted according to the user's emotions.

[0736] This system efficiently and emotionally supports users in seeking legal advice. The user begins by entering their legal consultation or question in natural language into their terminal. The user's terminal then sends the input data to a server. This transmission process typically utilizes the internet, and encryption technology is used to ensure secure data transmission.

[0737] The server uses natural language processing techniques to analyze the received input data. This technique identifies important legal terms and contexts. Morphological and contextual analysis algorithms are typically used for the analysis. Next, the server consults a knowledge base to extract legal information relevant to the input data. The knowledge base includes comprehensive legal codes and case law, and this information forms the basis for legal advice to the user.

[0738] Furthermore, the server also takes emotional factors into account. Using an emotion engine, it analyzes and identifies the emotions expressed by the user. Emotions such as anxiety, anger, and relief are extracted from the data, and the tone of the legal advice provided is adjusted accordingly.

[0739] As a concrete example, consider a case where a user enters, "I need advice regarding sexual harassment at work. I'm feeling anxious." The server analyzes this input, collecting legally relevant information while simultaneously recognizing the user's anxiety. Based on this, it generates advice in a tone such as, "Your rights are protected by law. Please rest assured," and sends it to the user's device.

[0740] This system uses a generative AI model to provide users with a safe and secure environment for legal consultations. Examples of prompts include, "I want legal advice regarding a workplace problem. What procedures should I follow?" In this way, users can receive support to address legal issues quickly and effectively.

[0741] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0742] Step 1:

[0743] The user inputs legal advice or questions into the terminal using natural language. The input data from the user is in text format, and the terminal receives this data and prepares to send it to the server. This step forms the basis for information gathering by the user.

[0744] Step 2:

[0745] The terminal sends input data received from the user to the server. The transmitted data is securely encrypted and delivered to the server via the internet connection. A special communication protocol is used during this process to maintain data integrity.

[0746] Step 3:

[0747] The server receives input data sent from the terminal and begins analysis using natural language processing techniques. The text data received as input is broken down by morphological analysis, and legal terms and related keywords are extracted. The analyzed information is then used for querying in the next step.

[0748] Step 4:

[0749] The server searches a knowledge base based on the analyzed keywords and contextual information. This knowledge base includes legal codes and case law data, serving as a foundation for querying relevant legal information. As output, legal information related to the user's inquiry is extracted and proceeds to the next generation process.

[0750] Step 5:

[0751] The server uses an emotion engine to analyze the user's emotional elements from the input data. Here, it identifies the user's emotions from the linguistic structure and vocabulary within the text, extracting emotional characteristics such as anxiety and reassurance. As output, this emotional information is used in the advice generation process.

[0752] Step 6:

[0753] The server generates legal advice using natural language generation technology, based on pre-extracted legal and emotional information. During this generation process, it adjusts the tone according to the user's emotions while constructing appropriate advice. The output is legal advice presented in a format that is easy for the user to understand.

[0754] Step 7:

[0755] The generated legal advice is sent from the server to the user's terminal. The user can receive this advice on their terminal and use it to assist in their legal consultation. The display interface is designed to make the advice easy for the user to read.

[0756] (Application Example 2)

[0757] 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".

[0758] When users seek legal advice, it is essential to provide appropriate legal advice based solely on the content of their inquiry. However, responses that disregard the user's emotional state can hinder the user experience. Traditional legal consultation systems focus on providing legal information but lack consideration for the user's emotional needs. Therefore, it is necessary to enhance user confidence and trust by appropriately adjusting legal consultation responses to the user's emotions.

[0759] 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.

[0760] In this invention, the server includes means for receiving legal-related input information from the user, means for analyzing the input information using natural language processing technology to identify legal-related keywords and context, and sentiment analysis technology for analyzing the user's emotions from the input information. This makes it possible to provide consistent legal consultation that takes into account not only the user's legal needs but also their emotional state.

[0761] A "user terminal" is a computer device used by users to input the details of their legal consultation and communicate with the server.

[0762] "Natural language processing technology" is a technique for converting text data into a form that computers can understand and then analyzing it.

[0763] "Legal keywords and context" refers to important legal terms and their meanings found within the input information.

[0764] "Emotion analysis technology" is a technology that identifies and analyzes emotions from text input by users.

[0765] A "legal database" is a collection of electronic data containing legal information such as legal codes and precedents.

[0766] "Natural language generation technology" is a technology that generates sentences that are natural and easy for humans to understand, based on information that a computer has understood.

[0767] "Legal consultation answers" refer to solutions and advice provided to users regarding their legal questions and problems.

[0768] "User-appropriate tone" refers to a tone and expression that is appropriate to the user's emotions and situation.

[0769] This invention describes embodiments for carrying out this invention. This system is configured with a server at its core that interacts with a user terminal for legal consultation. When a user inputs legal consultation information into the user terminal, that information is sent to the server. The server first analyzes the input information using natural language processing technology to identify legal-related keywords and context. For example, a computing device running an NLP library is used for this purpose.

[0770] Next, the user's emotions are analyzed using emotion analysis technology. This analysis utilizes emotion analysis engines (e.g., IBM Watson, Google Cloud Natural Language API) to extract emotions from the input text. Once emotions are identified, legal databases and past case databases are queried based on the analysis results to extract relevant legal information. This involves using database software that includes legal codes and case law data.

[0771] Based on extracted legal information and sentiment analysis results, natural language generation technology is used to generate legal advice responses in a tone appropriate to the user. The generated responses are sent to the user's terminal and displayed. A natural language generation engine (e.g., OpenAI's GPT series) is used in this process.

[0772] As a concrete example, consider a case where a user enters a legal consultation request stating, "I am worried about a problem at work." The system senses this anxiety and generates appropriate, emotionally responsive advice such as, "The problem is protected by law, so please rest assured. Here's how you should proceed next." In this way, the system considers the user's emotions during the legal consultation process, enabling it to provide more humane and reliable responses.

[0773] An example of a prompt for the generating AI model is as follows: "The user is expressing concern about noise problems with their neighbor. Please generate a response that provides reassurance while also outlining legal solutions."

[0774] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0775] Step 1:

[0776] The user inputs the content of their legal consultation into their terminal using natural language. The entered text information is sent directly to the server; therefore, the primary input is the legal consultation text. The output is the text sent to the server.

[0777] Step 2:

[0778] The server analyzes the received text information using natural language processing (NLP) techniques. Specifically, it uses an NLP library to extract legal keywords and context. This process outputs specific terms related to the legal context.

[0779] Step 3:

[0780] The server analyzes the user's emotions using emotion analysis technology based on the parsed text information. Specifically, it uses an emotion analysis engine to identify emotions such as "anxiety," "relief," and "anger." The output of this process is data indicating the user's emotions.

[0781] Step 4:

[0782] The server queries legal databases and past case databases using legal keywords and sentiment data. It extracts appropriate legal information from the databases and outputs the relevant information.

[0783] Step 5:

[0784] The server uses extracted legal information and sentiment data to generate legal advice responses for the user using natural language generation technology. This process utilizes a generative AI model to create output that corresponds to the prompt text. The generated responses have a tone that matches the user's emotions.

[0785] Step 6:

[0786] The server sends the generated response to the user's terminal. The output response is presented to the user through the user interface, allowing the user to visually confirm it.

[0787] 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.

[0788] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] The inside of the Emotion Map 400 represents what's in your mind, while the outside represents what you're doing. Therefore, the further you go out the 400-coordinate scale, the more visible your emotions become (the more they manifest in your actions).

[0794] 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.

[0795] 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."

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] The following is further disclosed regarding the embodiments described above.

[0809] (Claim 1)

[0810] A means of receiving legal input information from a user terminal,

[0811] The aforementioned input information is analyzed using natural language processing technology to identify legal keywords and contexts,

[0812] A means of querying legal databases and past case databases based on the analysis results and extracting relevant legal information,

[0813] A means of generating legal advice answers for users using natural language generation technology based on extracted legal information,

[0814] Means for transmitting the generated response to the user terminal,

[0815] A system that includes this.

[0816] (Claim 2)

[0817] The system according to claim 1, wherein the aforementioned legal database has a function to provide more accurate legal information by linking with the complete collection of laws and a case law database.

[0818] (Claim 3)

[0819] The system according to claim 1, wherein the response generation means includes natural language technology for converting legal terms into simple language and providing information in a form that is easy for the user to understand.

[0820] "Example 1"

[0821] (Claim 1)

[0822] Means for obtaining legal information from user devices,

[0823] The aforementioned information is analyzed using language processing technology, and means are used to identify legally relevant indicators and background information.

[0824] A means of retrieving relevant legal information by referring to a legal information database and a past case information database based on the analysis results,

[0825] A means of generating answers to legal consultations for the user using language generation technology based on extracted legal information,

[0826] Means for transmitting the generated response to the user device,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, wherein the aforementioned legal information base has a function to provide more accurate legal information in cooperation with legal books and case law information bases.

[0830] (Claim 3)

[0831] The system according to claim 1, wherein the response generation means includes language technology for replacing legal terminology with easily understandable expressions and providing information in a format that is easy for the user to understand.

[0832] "Application Example 1"

[0833] (Claim 1)

[0834] A means of obtaining user voice input,

[0835] A means for converting the aforementioned voice input into text data using speech recognition technology,

[0836] A means for analyzing the aforementioned text data using natural language processing technology to identify legal keywords and contexts,

[0837] A means of querying legal databases and past case databases based on the analysis results and extracting relevant legal information,

[0838] A means of generating voice responses to legal consultations for users using speech synthesis technology based on extracted legal information,

[0839] A means of providing the generated response to the user device via voice,

[0840] A system that includes this.

[0841] (Claim 2)

[0842] The system according to claim 1, wherein the aforementioned legal database has a function to provide accurate legal information in conjunction with standards and case law databases.

[0843] (Claim 3)

[0844] The system according to claim 1, wherein the response generation means includes natural language technology for converting legal terms into easily understandable expressions and providing information in a format that is easy for the user to understand.

[0845] "Example 2 of combining an emotion engine"

[0846] (Claim 1)

[0847] A means of receiving legal input data from a user terminal,

[0848] A means for analyzing the aforementioned input data using natural language processing technology to identify relevant terms and contexts,

[0849] A means for querying knowledge bases and record bases based on analysis results and extracting relevant information,

[0850] A means of generating legal advice using natural language generation technology based on extracted information,

[0851] Means for transmitting the generated advice to the user terminal,

[0852] A means of adjusting the tone of advice based on the analyzed emotional elements,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] The system according to claim 1, wherein the knowledge base has a function to provide more precise information in conjunction with a comprehensive legal code and case law database.

[0856] (Claim 3)

[0857] The system according to claim 1, wherein the advice generation means includes natural language technology that converts technical terms into simple language and responds to the user's emotional response.

[0858] "Application example 2 when combining with an emotional engine"

[0859] (Claim 1)

[0860] A means of receiving legal input information from a user terminal,

[0861] The aforementioned input information is analyzed using natural language processing technology to identify legal keywords and contexts,

[0862] Emotion analysis technology that analyzes user emotions from input information,

[0863] A means of querying legal databases and past case databases based on the analysis results and extracting relevant legal information,

[0864] A means of generating legal consultation responses in a tone appropriate to the user using natural language generation technology, based on extracted legal information and sentiment analysis results,

[0865] Means for transmitting the generated response to the user terminal,

[0866] A system that includes this.

[0867] (Claim 2)

[0868] The system according to claim 1, wherein the legal database has a function to provide more accurate legal information in conjunction with a legal code and case law database, and also has a function to add support information that responds to the user's emotions.

[0869] (Claim 3)

[0870] The system according to claim 1, wherein the response generation means includes natural language technology for converting legal terminology into simple language, providing information in a format easily understandable to the user, and including comforting words that are in line with the user's feelings. [Explanation of symbols]

[0871] 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. A means of obtaining user voice input, A means for converting the aforementioned voice input into text data using speech recognition technology, A means for analyzing the aforementioned text data using natural language processing technology to identify legal keywords and contexts, A means of querying legal databases and past case databases based on the analysis results and extracting relevant legal information, A means of generating voice responses to legal consultations for users using speech synthesis technology based on extracted legal information, A means of providing the generated response to the user device via voice, A system that includes this.

2. The system according to claim 1, wherein the aforementioned legal database has a function to provide accurate legal information in conjunction with standards and case law databases.

3. The system according to claim 1, wherein the response generation means includes natural language technology for converting legal terms into easily understandable expressions and providing information in a format that is easy for the user to understand.

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