system

Abstract

We provide the system. [Solution] A means of providing legal advice using generative artificial intelligence, A means of receiving legal consultations via a communication terminal, A means of generating legal advice based on the content of the consultation received, Means for transmitting generated legal advice, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] When an individual faces a legal problem, there is a problem that it is difficult to obtain legal advice quickly and easily. In conventional legal consultations, access to experts is limited, and it is often difficult to use due to cost and time constraints. In addition, it is difficult for an individual without specialized legal knowledge to collect information on their own and obtain appropriate advice. In such a situation, there is a need for a means to provide legal consultations efficiently and at an affordable price.

Means for Solving the Problems

[0005] The present invention solves the above problems by providing a system that receives legal consultation content via a communication terminal, generates legal advice based on the consultation content using artificial intelligence, and transmits the generated advice. Specifically, it provides an environment in which users can easily consult even without specialized legal knowledge, and further includes a function to establish a connection with human legal professionals, enabling a rapid response even to particularly complex cases. This system is configured to reduce the financial burden and suit a wide range of users by offering multiple pricing plans to meet the needs of users.

[0006] "Generative artificial intelligence" is an artificial intelligence technology that generates information tailored to a specific purpose based on input data, and provides advice or answers to users.

[0007] A "communication terminal" is an electronic device used by users to send and receive information via a network such as the internet.

[0008] "Means of providing legal advice" refers to the processes and techniques for providing answers and guidance to legal issues and questions related to law.

[0009] A "human legal professional" is a professional who possesses specialized legal knowledge and qualifications and provides support for legal consultations and legal procedures.

[0010] A "pricing plan" is a system that shows the cost structure for users when using a service, and prices are set to suit different usage needs. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3]This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] 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.

[0016] 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, and the like.

[0017] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0018] 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."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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".

[0032] This invention is a system that provides legal advice using generative artificial intelligence, and its implementation requires multiple components. The system operates with a communication terminal and a server as its main components, providing an environment in which users can easily seek legal advice.

[0033] First, the user accesses the legal consultation system from their device. The communication device is connected to the internet and receives the consultation information entered by the user and transmits it to the server. The user can enter specific questions and situations related to legal issues.

[0034] Next, the server processes the received consultation request. Using artificial intelligence, the server generates optimal legal advice based on the input information. The AI ​​references the latest laws and precedents from legal databases to create advice tailored to the user's situation. This process is automated, enabling the provision of fast and accurate legal advice.

[0035] Once advice is generated, the server sends the results to the user via a communication terminal. At this point, the user can review the advice on the terminal and enter additional questions if necessary. Furthermore, if the user has a complex legal issue, the server can connect them with a human legal expert it has partnered with.

[0036] This system offers multiple pricing plans to enhance user convenience, with each plan providing a different level of service. This allows users to choose the plan that best suits their needs and budget. For example, the basic plan includes only AI-powered legal advice, while the advanced plan also allows consultation with human legal professionals.

[0037] For example, if a user wants advice regarding labor law, they input their work-related issues, and the server instantly generates legally compliant advice and sends it to their terminal. Based on this advice, the user can decide on their next steps. For instance, in more complex cases, the system may suggest the option of consulting with an expert.

[0038] By implementing these functions, users can quickly obtain necessary legal advice without being constrained by time or geographical limitations, and the system enables the efficient provision of legal consultations.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user accesses the legal consultation system using a communication device. They log in to the system by entering their username and password on the login screen displayed on the device.

[0042] Step 2:

[0043] The terminal displays a screen to the logged-in user, allowing them to select a legal consultation category (e.g., civil law, criminal law, labor law, etc.). The user chooses the area they wish to consult about and enters the details of their consultation into the text box.

[0044] Step 3:

[0045] The server receives the consultation content and selected category sent from the terminal. It then invokes a generating artificial intelligence to analyze the received content and extract the necessary legal knowledge.

[0046] Step 4:

[0047] The server uses artificial intelligence to generate optimal advice based on the input. The generation process references the latest legal information and relevant case precedents to create advice tailored to the user's specific needs.

[0048] Step 5:

[0049] The server sends the generated legal advice to the communication terminal. The terminal displays the results to the user and provides buttons for additional questions or confirmations.

[0050] Step 6:

[0051] The user reviews the advice and enters any further questions or concerns. This information is sent to the server via the device.

[0052] Step 7:

[0053] The server calls the AI ​​generator again based on the additional information and updates the advice. It then sends the newly generated advice to the terminal, providing feedback to the user.

[0054] Step 8:

[0055] If the situation is complex and requires more specialized assistance, the server will suggest connecting the user with a partner human legal expert. It will collect preferred meeting dates and details, and coordinate between the expert and the user.

[0056] Step 9:

[0057] When a user wants to select or change their pricing plan, they choose their desired plan from the list of plans displayed on their device and enter their payment information. This information is processed on the server, and the plan settings are updated.

[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] Traditional legal consultations primarily involved face-to-face meetings with experts, which presented problems such as time and location constraints and high costs. This resulted in a challenge for many people, making it difficult to obtain quick and convenient legal advice when needed.

[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 providing legal advice using generative artificial intelligence, means for receiving legal consultation information via an information processing device, and means for generating legal advice based on the received consultation information by referring to an information database. This enables users to obtain legal advice quickly and efficiently without being constrained by time or geographical limitations.

[0063] "Generative artificial intelligence" is a technology that generates new information based on input data and provides advice and solutions to specific problems.

[0064] An "information processing device" is a device that can receive, process, and transmit digital information, and plays a role in data communication between the user and the system.

[0065] "Consultation information" refers to specific data and questions that users provide to the system in order to resolve legal questions and problems.

[0066] An "information database" is a digital repository in which legal regulations, precedents, and other reference information are organized and stored, and is used as reference material for generating legal advice.

[0067] A "pricing menu" refers to a pricing structure designed to allow users to choose the plan that best suits them from multiple usage plans offered within the system.

[0068] This invention is implemented as a system that provides legal advice using generative artificial intelligence. The main components of the system are the user's terminal and the server. The user accesses the legal consultation system using their terminal and inputs specific legal consultation information. The terminal is connected to the internet and transmits this input information to the server. For example, the user can input a prompt such as, "Please tell me about the termination clause in the contract."

[0069] Next, the server processes the received consultation information. Specifically, the server is equipped with a generative AI model that analyzes the user's input. This analysis uses natural language processing technology to convert text information into a machine-understandable format. The server then searches for relevant laws and precedents by referring to a legal database and uses the generative AI model to generate optimal legal advice. This database contains a wide range of information on all aspects of law and serves as reference material necessary for generating advice.

[0070] The generated legal advice is sent from the server to the user's terminal, and the user can view the displayed advice. For example, if a user asks about "points to keep in mind when taking paid leave," the server uses its relevant legal database to create appropriate advice and provides it to the user via their terminal. The user can then decide on their next course of action based on this information and can enter further detailed questions if necessary.

[0071] This system enables a fast and efficient legal consultation and advice process, allowing users to access necessary information regardless of geographical constraints. To this end, multiple pricing options are available to suit individual user needs, and further support may be offered through the selection of the appropriate plan.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] Users access the legal consultation system from their devices and input specific legal questions or situations. The prompts they enter might include phrases like "points to note when taking paid leave." This information is received by the device and formatted for transmission to the server. The output is the formatted data.

[0075] Step 2:

[0076] The terminal sends this formatted data to the server using a secure protocol. The data sent is text information containing specific details of the consultation. The output is data in a format that the server can receive.

[0077] Step 3:

[0078] The server receives data sent from the terminal. It takes the received data as input and first converts it into a format suitable for the generated AI model. This is done using natural language processing techniques. The output is data in a format that can be input into the AI ​​model.

[0079] Step 4:

[0080] The server searches the information database based on the converted data and collects relevant legal information. This search finds the latest laws and precedents. The output is highly relevant legal information.

[0081] Step 5:

[0082] The server uses a generative AI model to generate optimal legal advice based on collected legal information and in response to user input. A multi-layer neural network is used in this process. The output is the generated legal advice text.

[0083] Step 6:

[0084] The server sends the generated legal advice to the user's terminal. At this time, the output is formatted to a format viewable on the terminal. The output is formatted legal advice data for the user's terminal.

[0085] Step 7:

[0086] The terminal displays legal advice received from the server to the user. In the user interface, the advice is presented in a clear and organized format. The user uses this information to decide on their next course of action and enters additional questions if they require further details. The output is the legal advice information viewed by the user.

[0087] (Application Example 1)

[0088] 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."

[0089] With the increase in consumer transactions on online platforms, the legal issues consumers face are becoming more complex. However, there is a lack of quick and easy access to expert legal advice, making it difficult to properly address issues, particularly those related to returns and warranties.

[0090] 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.

[0091] In this invention, the server includes means for providing legal advice using generative artificial intelligence, means for identifying and providing advice on legal issues, and means for referencing information from legal databases related to an online platform. This enables consumers to obtain quick and accurate legal advice.

[0092] "Generative artificial intelligence" is an artificial system that has the ability to automatically generate legal advice based on the input content of the consultation.

[0093] A "communication device" is hardware or software that receives legal consultations from users via the internet and transmits them to a server.

[0094] "Means of generating legal advice" refers to the process of creating optimal legal advice by referencing information from legal databases based on the content of the consultation received.

[0095] A "legal database" is a collection of data containing the latest laws and precedents, and is a resource that generating AI refers to in order to provide appropriate advice.

[0096] "Means of identifying legal issues related to consumer transactions" refers to an analytical process for understanding the legal issues faced by users and providing specific legal advice.

[0097] To implement this invention, the user first accesses the legal consultation system using a communication terminal and inputs their consultation details. The terminal is connected to the internet and has the function of sending the user's inputted legal consultation to a server. The server is equipped with generating artificial intelligence and analyzes the received consultation details, referring to the latest laws and precedents contained in the legal database to identify legal issues related to delivery. Based on this, it generates appropriate legal advice and sends it to the user via the terminal. The server also has the ability to focus on specific legal issues related to consumer transactions and provide highly accurate advice on issues concerning returns and warranties.

[0098] This system utilizes Google Cloud's generative AI model to quickly and accurately generate advice by processing legal data. For example, when a user seeks advice regarding the return of a purchased item, the prompt might read: "I have an item I would like to return, but the refund conditions are unclear. Please advise me on the legal steps I should take regarding the return and refund of this item." In this context, the generative AI model generates optimal advice, allowing the user to choose the appropriate course of action based on that advice.

[0099] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0100] Step 1:

[0101] The user accesses the legal consultation system using a communication terminal and enters specific details of their consultation. The entered data includes detailed information about the user's legal questions and problems. The terminal receives this input and prepares to send it to the server via the internet.

[0102] Step 2:

[0103] The server receives legal consultation details sent by the user. The received data includes the user's specific legal problem, and the server uses this data to prepare an access request to a legal database. The server analyzes and transforms the data, preparing it in a format that can be input into an AI model.

[0104] Step 3:

[0105] The server uses generative artificial intelligence to process the converted legal consultation content. The AI ​​references relevant laws and precedents from legal databases to generate the best advice for the user's legal problem. This data processing includes text analysis and the application of legal knowledge. The generated advice is then compiled into a new dataset.

[0106] Step 4:

[0107] The server sends the generated legal advice to the communication terminal. The terminal displays the requested advice to the user, who then reviews it to obtain information to decide on their next course of action. In this step, data transformation is performed to present the generated advice in a format that is easy for the user to understand.

[0108] 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.

[0109] This invention provides a system for conducting legal consultations efficiently and effectively, and by incorporating an emotion engine, it offers advice that takes into account the user's emotional state. The system mainly consists of a communication terminal, a server, a generative artificial intelligence, and an emotion engine.

[0110] First, the user accesses the legal consultation system using a communication terminal. At this time, the emotion engine analyzes the user's emotions from the input text and voice. The emotion engine determines the user's emotional state from their words and actions and the language they use, and sends this data to the server.

[0111] The server uses artificial intelligence to generate personalized advice based on received emotional data and legal consultation content. The tone and content of the advice are automatically adjusted to match the emotions recognized by the emotion engine. For example, if the user is feeling anxious, the consultation will include encouragement.

[0112] The generated advice is sent back to the communication terminal and provided to the user. The display format is customized to the user's emotional state, making it possible to design a UI that is visually and emotionally considerate.

[0113] Furthermore, if the emotion engine strongly indicates that the user is experiencing a specific emotional state (e.g., stress, tension), the server will suggest connecting the user with a human legal expert. The user will input their preferred date and time for the expert meeting and other details via their communication terminal, and the server will then coordinate the connection with the expert based on this information.

[0114] As a concrete example, consider a situation where a user is deeply troubled by a work-related issue. In this case, the emotion engine detects anxiety and impatience from the user's text. Based on this, the server can generate appropriate advice and suggest a consultation with a specialist as an option. This allows the user to gain a sense of security and receive support to take more appropriate action.

[0115] This system can significantly improve the legal consultation experience by recognizing the user's emotions and promptly providing appropriate legal advice and necessary support.

[0116] The following describes the processing flow.

[0117] Step 1:

[0118] The user accesses the legal consultation system using a communication device. They enter their username and password on the login screen and log in to the system.

[0119] Step 2:

[0120] The device displays a screen for selecting a legal consultation category. The user chooses the legal field they wish to consult about, enters their consultation details, and presses the submit button.

[0121] Step 3:

[0122] The terminal sends the user's input to the server for analysis. Simultaneously, the emotion engine performs emotion analysis based on the user's input.

[0123] Step 4:

[0124] The server retrieves the consultation content and emotional data received from the communication terminal. First, it checks the results analyzed by the emotion engine to understand the user's emotional state.

[0125] Step 5:

[0126] The server uses artificial intelligence to generate optimal legal advice based on the consultation content and emotional data. At this time, the tone and content of the advice are adjusted according to the emotional data.

[0127] Step 6:

[0128] The server sends the generated advice to the communication terminal. The terminal displays the legal advice tailored to the user.

[0129] Step 7:

[0130] The user reviews the advice and enters it again if they have additional questions or require further information. This causes the device to send the new information to the server.

[0131] Step 8:

[0132] Depending on the complexity of the situation and the user's emotional state, the server will suggest a meeting with a human legal expert. The user enters their preferred date and time and provides details for the connection.

[0133] Step 9:

[0134] Based on the user's request, the server coordinates schedules with affiliated legal professionals and confirms the meeting. The user participates in the meeting via a communication device.

[0135] (Example 2)

[0136] 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".

[0137] Traditional legal consultation systems often provide formal advice in response to the consultation content, and have the drawback of not being able to respond flexibly to the user's emotional state. Furthermore, even when the user is experiencing strong emotions, there is a problem in smoothly coordinating with experts.

[0138] 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.

[0139] In this invention, the server includes means for providing legal advice using a generation engine, means for receiving legal consultation content via an information processing device, and means incorporating an emotion engine for analyzing the user's emotions. This enables the rapid provision of accurate legal advice tailored to the user's emotional state, as well as smooth collaboration with legal professionals as needed.

[0140] A "generative engine" refers to software that uses a learning algorithm to generate legal advice based on input data.

[0141] An "information processing device" is a device used by users for communication, and includes hardware and software capable of receiving and processing legal consultation content.

[0142] An "emotion engine" is a function or program that analyzes the user's emotional state from their input, and is used to provide appropriate responses and adjustments based on that data.

[0143] A "legal expert" is a human professional with deep knowledge and experience in law, who can provide more specialized advice to users seeking assistance.

[0144] "Emotional data" refers to information indicating the emotional state, analyzed by the emotion engine from user input, and is used when adjusting the content and tone of legal advice.

[0145] "Adjusting the tone of advice" refers to the process of changing the tone and expression of legal advice provided to match the user's emotional state, in order to provide a more appropriate and empathetic response.

[0146] This invention is a system for providing advice that takes into account the emotional aspects when a user seeks legal advice. The system consists of an information processing device, a server, a generation engine, and an emotion engine.

[0147] The user first accesses the legal consultation system via an information processing device. This device is a standard computing device that communicates with the server via an internet connection. The user then inputs the specific details of their legal consultation in text or voice.

[0148] The communication terminal then sends this input to the emotion engine. The emotion engine uses text analysis and speech analysis techniques to identify the user's emotional state. The natural language processing techniques used analyze the user's word choice and tone of voice.

[0149] The server uses a generative engine based on received sentiment data to generate legal advice. The generative engine employs a generative AI model that has been pre-trained with legal data. The tone and content of the generated legal advice are adjusted according to the data from the sentiment engine. For example, if the user is feeling stressed, the advice will be generated in a more reassuring tone.

[0150] The generated advice is sent back to the communication terminal and presented to the user. At this point, the advice is displayed visually through a user interface customized according to the user's emotional state. In particular, designs aimed at alleviating tension are sometimes employed.

[0151] For example, if a user seeks advice about anxieties related to work issues, the emotion engine may recognize the anxious feelings, and the generation engine may generate advice such as, "Don't worry. This problem is solvable. There are several options."

[0152] An example of a prompt message might be something like, "A system using a generation engine to provide emotionally sensitive legal advice to users who are anxious about labor issues." This would enable appropriate and emotionally sensitive legal support.

[0153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0154] Step 1:

[0155] Users access the legal consultation system using an information processing device and input their consultation details in text or voice. The data entered consists of the user's specific legal questions and descriptions of their situation. This constitutes the input for this process.

[0156] Step 2:

[0157] The communication terminal receives input from the user and sends it to the emotion engine. The emotion engine analyzes emotions from the input text or speech using natural language processing. Specifically, it identifies emotional states (e.g., anxiety, relief, anger). The result of this analysis becomes the output.

[0158] Step 3:

[0159] The server receives the analysis results from the emotion engine and uses the generation engine to generate legal advice. The input consists of the analyzed emotion data and the user's consultation content. The generation engine applies a learned algorithm using this data to create appropriate legal advice. The output is adjusted advice that takes the user's feelings into consideration.

[0160] Step 4:

[0161] The server then sends the generated advice back to the communication terminal. This transmission process is performed to present the advice to the user at an appropriate time. The output is customized advice tailored to the user's emotions.

[0162] Step 5:

[0163] The communication terminal displays advice sent from the server to the user. Specifically, it displays the advice on the user's device using a visually appealing interface. The output is presented in a user-friendly format, with the font size and color adjusted according to the user's emotional state.

[0164] Step 6:

[0165] If the emotion engine determines that the user's emotional state is particularly serious, the server will suggest connecting the user with a human legal expert. The user will specify preferred meeting dates and times, and this information will be used to coordinate with the expert. The output will include the specific date and time of the consultation and the progress of the consultation arrangement.

[0166] (Application Example 2)

[0167] 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".

[0168] This invention addresses the challenge of enabling personalized content recommendations in online content delivery that take into account the emotional state of users. Modern digital content delivery platforms are required to appropriately understand users' emotions and psychological states and provide appropriate content accordingly, but there is a problem in that no system adequately meets this need.

[0169] 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.

[0170] In this invention, the server includes means for determining the user's emotional state based on emotion analysis, means for adjusting the generated advice according to the emotional state, and means for providing recommendation information based on the emotional state. This makes it possible to automatically generate content appropriate to each user's emotions and improve the user experience.

[0171] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to autonomously make judgments and generate appropriate advice and recommendations based on user input information.

[0172] A "communication device" is a device that has the function of receiving information from users and transmitting output from the system to users.

[0173] "Emotional analysis" is a technology that determines and classifies a user's emotional state based on their input information. It is a process of understanding a user's psychological state by analyzing text and audio information.

[0174] "Emotional state" refers to information that indicates the user's psychological or emotional condition, and is expressed as a result of analysis by the system.

[0175] "Providing recommendations" refers to the act of suggesting personalized content and services based on the user's emotional state.

[0176] This invention is a system for realizing personalized content delivery based on the emotional state of users. The system mainly consists of a server and a communication device, and uses emotion analysis and generative AI models.

[0177] The server receives input data from the communication device. This data includes consultation content in text and audio formats. The server uses emotion analysis technology to determine the user's emotional state from this data. Specifically, it quickly extracts the user's emotional state through emotion recognition software. The results of the emotion recognition are processed within the server and stored as emotion data.

[0178] Next, the server utilizes a generative AI model to generate content tailored to the user's emotional state. This generation process selects appropriate information from a vast content database and presents it in the format best suited to the user. For example, if the system determines that the user wants to relax, it will recommend calming music or images of natural scenery.

[0179] The communication device presents the user with recommendation information sent from the server. This allows the user to seamlessly obtain content that suits their emotional state. For example, if a user inputs a voice message saying, "It was a stressful day," the system will recommend relaxation music or videos for viewing.

[0180] An example of a prompt from the generating AI model is: "Identify the emotion from the user's voice statement, 'It was a stressful day,' and recommend relaxation music or movies appropriate for that emotion." In this way, this system enables the recommendation of high-value content based on the user's emotions.

[0181] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0182] Step 1:

[0183] The user provides input information (e.g., text or voice) that influences their emotions through a communication device. The communication device sends this input data to the server. The input data contains information that indicates the user's emotional state.

[0184] Step 2:

[0185] The server uses emotion recognition software to analyze the received input data and identify the user's emotional state. This process extracts keywords and tones from the input data, and based on these, classifies the emotion (e.g., stress, anxiety, relaxation). The analysis results are stored on the server as emotional data.

[0186] Step 3:

[0187] The server uses a generative AI model based on the analyzed emotional data to generate content tailored to the user. In this step, emotional data is used as input, and individually optimized recommendation content is selected from a vast amount of content in the database. For example, music or videos that promote relaxation may be selected.

[0188] Step 4:

[0189] The server sends recommendation information for the generated content to the communication device. The communication device receives this information and presents it to the user. The presented content is fed back to the user visually or audibly, allowing the user to view or listen to content that matches their emotional state.

[0190] Step 5:

[0191] Users can view the presented content and, based on that experience, send feedback to the server via their communication device for future use. This feedback information is stored on the server and used for sentiment analysis and content generation in the future, thereby contributing to the provision of even more personalized experiences.

[0192] 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.

[0193] 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.

[0194] 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.

[0195] [Second Embodiment]

[0196] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0197] 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.

[0198] 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).

[0199] 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.

[0200] 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.

[0201] 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).

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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".

[0208] This invention is a system that provides legal advice using generative artificial intelligence, and its implementation requires multiple components. The system operates with a communication terminal and a server as its main components, providing an environment in which users can easily seek legal advice.

[0209] First, the user accesses the legal consultation system from their device. The communication device is connected to the internet and receives the consultation information entered by the user and transmits it to the server. The user can enter specific questions and situations related to legal issues.

[0210] Next, the server processes the received consultation request. Using artificial intelligence, the server generates optimal legal advice based on the input information. The AI ​​references the latest laws and precedents from legal databases to create advice tailored to the user's situation. This process is automated, enabling the provision of fast and accurate legal advice.

[0211] Once advice is generated, the server sends the results to the user via a communication terminal. At this point, the user can review the advice on the terminal and enter additional questions if necessary. Furthermore, if the user has a complex legal issue, the server can connect them with a human legal expert it has partnered with.

[0212] This system offers multiple pricing plans to enhance user convenience, with each plan providing a different level of service. This allows users to choose the plan that best suits their needs and budget. For example, the basic plan includes only AI-powered legal advice, while the advanced plan also allows consultation with human legal professionals.

[0213] For example, if a user wants advice regarding labor law, they input their work-related issues, and the server instantly generates legally compliant advice and sends it to their terminal. Based on this advice, the user can decide on their next steps. For instance, in more complex cases, the system may suggest the option of consulting with an expert.

[0214] By implementing these functions, users can quickly obtain necessary legal advice without being constrained by time or geographical limitations, and the system enables the efficient provision of legal consultations.

[0215] The following describes the processing flow.

[0216] Step 1:

[0217] The user accesses the legal consultation system using a communication device. They log in to the system by entering their username and password on the login screen displayed on the device.

[0218] Step 2:

[0219] The terminal displays a screen to the logged-in user, allowing them to select a legal consultation category (e.g., civil law, criminal law, labor law, etc.). The user chooses the area they wish to consult about and enters the details of their consultation into the text box.

[0220] Step 3:

[0221] The server receives the consultation content and selected category sent from the terminal. It then invokes a generating artificial intelligence to analyze the received content and extract the necessary legal knowledge.

[0222] Step 4:

[0223] The server uses artificial intelligence to generate optimal advice based on the input. The generation process references the latest legal information and relevant case precedents to create advice tailored to the user's specific needs.

[0224] Step 5:

[0225] The server sends the generated legal advice to the communication terminal. The terminal displays the results to the user and provides buttons for additional questions or confirmations.

[0226] Step 6:

[0227] The user reviews the advice and enters any further questions or concerns. This information is sent to the server via the device.

[0228] Step 7:

[0229] The server calls the AI ​​generator again based on the additional information and updates the advice. It then sends the newly generated advice to the terminal, providing feedback to the user.

[0230] Step 8:

[0231] If the situation is complex and requires more specialized assistance, the server will suggest connecting the user with a partner human legal expert. It will collect preferred meeting dates and details, and coordinate between the expert and the user.

[0232] Step 9:

[0233] When a user wants to select or change their pricing plan, they choose their desired plan from the list of plans displayed on their device and enter their payment information. This information is processed on the server, and the plan settings are updated.

[0234] (Example 1)

[0235] 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."

[0236] Traditional legal consultations primarily involved face-to-face meetings with experts, which presented problems such as time and location constraints and high costs. This resulted in a challenge for many people, making it difficult to obtain quick and convenient legal advice when needed.

[0237] 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.

[0238] In this invention, the server includes means for providing legal advice using generative artificial intelligence, means for receiving legal consultation information via an information processing device, and means for generating legal advice based on the received consultation information by referring to an information database. This enables users to obtain legal advice quickly and efficiently without being constrained by time or geographical limitations.

[0239] "Generative artificial intelligence" is a technology that generates new information based on input data and provides advice and solutions to specific problems.

[0240] An "information processing device" is a device that can receive, process, and transmit digital information, and plays a role in data communication between the user and the system.

[0241] "Consultation information" refers to specific data and questions that users provide to the system in order to resolve legal questions and problems.

[0242] An "information database" is a digital repository in which legal regulations, precedents, and other reference information are organized and stored, and is used as reference material for generating legal advice.

[0243] A "pricing menu" refers to a pricing structure designed to allow users to choose the plan that best suits them from multiple usage plans offered within the system.

[0244] This invention is implemented as a system that provides legal advice using generative artificial intelligence. The main components of the system are the user's terminal and the server. The user accesses the legal consultation system using their terminal and inputs specific legal consultation information. The terminal is connected to the internet and transmits this input information to the server. For example, the user can input a prompt such as, "Please tell me about the termination clause in the contract."

[0245] Next, the server processes the received consultation information. Specifically, the server is equipped with a generative AI model that analyzes the user's input. This analysis uses natural language processing technology to convert text information into a machine-understandable format. The server then searches for relevant laws and precedents by referring to a legal database and uses the generative AI model to generate optimal legal advice. This database contains a wide range of information on all aspects of law and serves as reference material necessary for generating advice.

[0246] The generated legal advice is sent from the server to the user's terminal, and the user can view the displayed advice. For example, if a user asks about "points to keep in mind when taking paid leave," the server uses its relevant legal database to create appropriate advice and provides it to the user via their terminal. The user can then decide on their next course of action based on this information and can enter further detailed questions if necessary.

[0247] This system enables a fast and efficient legal consultation and advice process, allowing users to access necessary information regardless of geographical constraints. To this end, multiple pricing options are available to suit individual user needs, and further support may be offered through the selection of the appropriate plan.

[0248] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0249] Step 1:

[0250] Users access the legal consultation system from their devices and input specific legal questions or situations. The prompts they enter might include phrases like "points to note when taking paid leave." This information is received by the device and formatted for transmission to the server. The output is the formatted data.

[0251] Step 2:

[0252] The terminal sends this formatted data to the server using a secure protocol. The data sent is text information containing specific details of the consultation. The output is data in a format that the server can receive.

[0253] Step 3:

[0254] The server receives data sent from the terminal. It takes the received data as input and first converts it into a format suitable for the generated AI model. This is done using natural language processing techniques. The output is data in a format that can be input into the AI ​​model.

[0255] Step 4:

[0256] The server searches the information database based on the converted data and collects relevant legal information. This search finds the latest laws and precedents. The output is highly relevant legal information.

[0257] Step 5:

[0258] The server uses a generative AI model to generate optimal legal advice based on collected legal information and in response to user input. A multi-layer neural network is used in this process. The output is the generated legal advice text.

[0259] Step 6:

[0260] The server sends the generated legal advice to the user's terminal. At this time, the output is formatted to a format viewable on the terminal. The output is formatted legal advice data for the user's terminal.

[0261] Step 7:

[0262] The terminal displays legal advice received from the server to the user. In the user interface, the advice is presented in a clear and organized format. The user uses this information to decide on their next course of action and enters additional questions if they require further details. The output is the legal advice information viewed by the user.

[0263] (Application Example 1)

[0264] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0265] With the increase in consumer transactions on online platforms, the legal issues consumers face are becoming more complex. However, there is a lack of quick and easy access to expert legal advice, making it difficult to properly address issues, particularly those related to returns and warranties.

[0266] 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.

[0267] In this invention, the server includes means for providing legal advice using generative artificial intelligence, means for identifying and providing advice on legal issues, and means for referencing information from legal databases related to an online platform. This enables consumers to obtain quick and accurate legal advice.

[0268] "Generative artificial intelligence" is an artificial system that has the ability to automatically generate legal advice based on the input content of the consultation.

[0269] A "communication device" is hardware or software that receives legal consultations from users via the internet and transmits them to a server.

[0270] "Means of generating legal advice" refers to the process of creating optimal legal advice by referencing information from legal databases based on the content of the consultation received.

[0271] A "legal database" is a collection of data containing the latest laws and precedents, and is a resource that generating AI refers to in order to provide appropriate advice.

[0272] "Means of identifying legal issues related to consumer transactions" refers to an analytical process for understanding the legal issues faced by users and providing specific legal advice.

[0273] To implement this invention, the user first accesses the legal consultation system using a communication terminal and inputs their consultation details. The terminal is connected to the internet and has the function of sending the user's inputted legal consultation to a server. The server is equipped with generating artificial intelligence and analyzes the received consultation details, referring to the latest laws and precedents contained in the legal database to identify legal issues related to delivery. Based on this, it generates appropriate legal advice and sends it to the user via the terminal. The server also has the ability to focus on specific legal issues related to consumer transactions and provide highly accurate advice on issues concerning returns and warranties.

[0274] This system uses Google Cloud's generative AI models to quickly and accurately generate advice by processing legal data. For example, when a user seeks advice regarding the return of a purchased item, the prompt might read: "I have an item I would like to return, but the refund conditions are unclear. Please tell me how I should legally handle the return and refund of this item." In this context, the generative AI model generates optimal advice, allowing the user to choose the appropriate course of action based on that advice.

[0275] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0276] Step 1:

[0277] The user accesses the legal consultation system using a communication terminal and enters specific consultation content. The input data includes the user's legal questions and detailed information about the issues. The terminal receives this input and prepares to transmit it to the server via the Internet.

[0278] Step 2:

[0279] The server receives the legal consultation content sent by the user. The received data contains the user's specific legal issues, and the server prepares an access request to the legal database based on this data. The server performs data analysis and conversion to format it into a form that can be input into the AI model.

[0280] Step 3:

[0281] The server uses a generative artificial intelligence to process the converted legal consultation content. The AI refers to relevant laws and regulations and case information from the legal database and generates the most appropriate advice for the user's legal issues. This data processing includes text analysis and the application of legal knowledge. The generated advice is composed as a new dataset.

[0282] Step 4:

[0283] The server transmits the generated legal advice to the communication terminal. The terminal displays the applied advice to the user, and the user can obtain information for determining the next action by viewing it. In this step, data conversion is performed to present the generated advice in a form that is easy for the user to understand.

[0284] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0285] The present invention is a system for efficiently and effectively providing legal consultations. By incorporating an emotion engine, it provides advice that takes into account the user's emotional state. The system is mainly composed of a communication terminal, a server, a generative artificial intelligence, and an emotion engine.

[0286] First, the user accesses the legal consultation system using a communication terminal. At this time, the emotion engine plays a role in analyzing the emotion from the user's input text and voice. The emotion engine judges the emotional state from the user's speech and the way of speaking used, and transmits it as data to the server.

[0287] Based on the received emotion data and the consultation content related to the law, the server utilizes the generative artificial intelligence to generate individual advice. The tone and content of the advice are automatically adjusted according to the emotion recognized by the emotion engine. For example, when the user is feeling anxious, provide a consultation that includes encouragement.

[0288] The generated advice is sent back to the communication terminal and provided to the user. The display form is customized according to the user's emotional state, and it is possible to design a UI that also takes emotions into account visually.

[0289] Furthermore, when a specific emotional state (e.g., stress, tension) is strongly indicated by the emotion engine for the user, the server proposes cooperation with a human legal expert. The user inputs the desired date and time for an interview with the expert and detailed information from the communication terminal, and the server adjusts the connection with the expert based on this.

[0290] As a specific example, consider a situation where the user is deeply troubled by a labor problem. In this case, the emotion engine detects anxiety and worry from the user's text. Based on this, the server can generate appropriate advice and propose an interview with an expert as an option. As a result, the user can gain a sense of security and receive support to be able to take more appropriate actions.

[0291] This system can significantly improve the legal consultation experience by recognizing the user's emotions and promptly providing appropriate legal advice and necessary support.

[0292] The following describes the processing flow.

[0293] Step 1:

[0294] The user accesses the legal consultation system using a communication device. They enter their username and password on the login screen and log in to the system.

[0295] Step 2:

[0296] The device displays a screen for selecting a legal consultation category. The user chooses the legal field they wish to consult about, enters their consultation details, and presses the submit button.

[0297] Step 3:

[0298] The terminal sends the user's input to the server for analysis. Simultaneously, the emotion engine performs emotion analysis based on the user's input.

[0299] Step 4:

[0300] The server retrieves the consultation content and emotional data received from the communication terminal. First, it checks the results analyzed by the emotion engine to understand the user's emotional state.

[0301] Step 5:

[0302] The server uses artificial intelligence to generate optimal legal advice based on the consultation content and emotional data. At this time, the tone and content of the advice are adjusted according to the emotional data.

[0303] Step 6:

[0304] The server sends the generated advice to the communication terminal. The terminal displays the legal advice tailored to the user.

[0305] Step 7:

[0306] If the user checks the advice and requests additional questions or further information, enter again. As a result, the terminal sends the new information to the server.

[0307] Step 8:

[0308] Depending on the complex situation and the user's emotional state, the server proposes an interview with a human legal expert. The user enters the desired date and time and provides details for the connection.

[0309] Step 9:

[0310] Based on the user's request, the server adjusts the schedule with the cooperating legal expert and finalizes the interview. The user participates in the interview through the communication terminal.

[0311] (Example 2)

[0312] Next, Example 2 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".

[0313] Conventional legal consultation systems often provide formal advice on the consultation content and have the problem that they cannot respond flexibly according to the user's emotional state. Also, there has been a problem that it is difficult to smoothly cooperate with experts even when the user has strong emotions.

[0314] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0315] In this invention, the server includes means for providing legal advice using a generation engine, means for receiving legal consultation content via an information processing device, and means incorporating an emotion engine for analyzing the user's emotions. This enables the rapid provision of accurate legal advice tailored to the user's emotional state, as well as smooth collaboration with legal professionals as needed.

[0316] A "generative engine" refers to software that uses a learning algorithm to generate legal advice based on input data.

[0317] An "information processing device" is a device used by users for communication, and includes hardware and software capable of receiving and processing legal consultation content.

[0318] An "emotion engine" is a function or program that analyzes the user's emotional state from their input, and is used to provide appropriate responses and adjustments based on that data.

[0319] A "legal expert" is a human professional with deep knowledge and experience in law, who can provide more specialized advice to users seeking assistance.

[0320] "Emotional data" refers to information indicating the emotional state, analyzed by the emotion engine from user input, and is used when adjusting the content and tone of legal advice.

[0321] "Adjusting the tone of advice" refers to the process of changing the tone and expression of legal advice provided to match the user's emotional state, in order to provide a more appropriate and empathetic response.

[0322] This invention is a system for providing advice that takes into account the emotional aspects when a user seeks legal advice. The system consists of an information processing device, a server, a generation engine, and an emotion engine.

[0323] The user first accesses the legal consultation system via an information processing device. This device is a standard computing device that communicates with the server via an internet connection. The user then inputs the specific details of their legal consultation in text or voice.

[0324] The communication terminal then sends this input to the emotion engine. The emotion engine uses text analysis and speech analysis techniques to identify the user's emotional state. The natural language processing techniques used analyze the user's word choice and tone of voice.

[0325] The server uses a generative engine based on received sentiment data to generate legal advice. The generative engine employs a generative AI model that has been pre-trained with legal data. The tone and content of the generated legal advice are adjusted according to the data from the sentiment engine. For example, if the user is feeling stressed, the advice will be generated in a more reassuring tone.

[0326] The generated advice is sent back to the communication terminal and presented to the user. At this point, the advice is displayed visually through a user interface customized according to the user's emotional state. In particular, designs aimed at alleviating tension are sometimes employed.

[0327] For example, if a user seeks advice about anxieties related to work issues, the emotion engine may recognize the anxious feelings, and the generation engine may generate advice such as, "Don't worry. This problem is solvable. There are several options."

[0328] An example of a prompt message might be something like, "A system using a generation engine to provide emotionally sensitive legal advice to users who are anxious about labor issues." This would enable appropriate and emotionally sensitive legal support.

[0329] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0330] Step 1:

[0331] Users access the legal consultation system using an information processing device and input their consultation details in text or voice. The data entered consists of the user's specific legal questions and descriptions of their situation. This constitutes the input for this process.

[0332] Step 2:

[0333] The communication terminal receives input from the user and sends it to the emotion engine. The emotion engine analyzes emotions from the input text or speech using natural language processing. Specifically, it identifies emotional states (e.g., anxiety, relief, anger). The result of this analysis becomes the output.

[0334] Step 3:

[0335] The server receives the analysis results from the emotion engine and uses the generation engine to generate legal advice. The input consists of the analyzed emotion data and the user's consultation content. The generation engine applies a learned algorithm using this data to create appropriate legal advice. The output is adjusted advice that takes the user's feelings into consideration.

[0336] Step 4:

[0337] The server then sends the generated advice back to the communication terminal. This transmission process is performed to present the advice to the user at an appropriate time. The output is customized advice tailored to the user's emotions.

[0338] Step 5:

[0339] The communication terminal displays advice sent from the server to the user. Specifically, it displays the advice on the user's device using a visually appealing interface. The output is presented in a user-friendly format, with the font size and color adjusted according to the user's emotional state.

[0340] Step 6:

[0341] If the emotion engine determines that the user's emotional state is particularly serious, the server will suggest connecting the user with a human legal expert. The user will specify preferred meeting dates and times, and this information will be used to coordinate with the expert. The output will include the specific date and time of the consultation and the progress of the consultation arrangement.

[0342] (Application Example 2)

[0343] 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."

[0344] This invention addresses the challenge of enabling personalized content recommendations in online content delivery that take into account the emotional state of users. Modern digital content delivery platforms are required to appropriately understand users' emotions and psychological states and provide appropriate content accordingly, but there is a problem in that no system adequately meets this need.

[0345] 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.

[0346] In this invention, the server includes means for determining the user's emotional state based on emotion analysis, means for adjusting the generated advice according to the emotional state, and means for providing recommendation information based on the emotional state. This makes it possible to automatically generate content appropriate to each user's emotions and improve the user experience.

[0347] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to autonomously make judgments and generate appropriate advice and recommendations based on user input information.

[0348] A "communication device" is a device that has the function of receiving information from users and transmitting output from the system to users.

[0349] "Emotional analysis" is a technology that determines and classifies a user's emotional state based on their input information. It is a process of understanding a user's psychological state by analyzing text and audio information.

[0350] "Emotional state" refers to information that indicates the user's psychological or emotional condition, and is expressed as a result of analysis by the system.

[0351] "Providing recommendations" refers to the act of suggesting personalized content and services based on the user's emotional state.

[0352] This invention is a system for realizing personalized content delivery based on the emotional state of users. The system mainly consists of a server and a communication device, and uses emotion analysis and generative AI models.

[0353] The server receives input data from the communication device. This data includes consultation content in text and audio formats. The server uses emotion analysis technology to determine the user's emotional state from this data. Specifically, it quickly extracts the user's emotional state through emotion recognition software. The results of the emotion recognition are processed within the server and stored as emotion data.

[0354] Next, the server utilizes a generative AI model to generate content tailored to the user's emotional state. This generation process selects appropriate information from a vast content database and presents it in the format best suited to the user. For example, if the system determines that the user wants to relax, it will recommend calming music or images of natural scenery.

[0355] The communication device presents the user with recommendation information sent from the server. This allows the user to seamlessly obtain content that suits their emotional state. For example, if a user inputs a voice message saying, "It was a stressful day," the system will recommend relaxation music or videos for viewing.

[0356] An example of a prompt from the generating AI model is: "Identify the emotion from the user's voice statement, 'It was a stressful day,' and recommend relaxation music or movies appropriate for that emotion." In this way, this system enables the recommendation of high-value content based on the user's emotions.

[0357] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0358] Step 1:

[0359] The user provides input information (e.g., text or voice) that influences their emotions through a communication device. The communication device sends this input data to the server. The input data contains information that indicates the user's emotional state.

[0360] Step 2:

[0361] The server uses emotion recognition software to analyze the received input data and identify the user's emotional state. This process extracts keywords and tones from the input data, and based on these, classifies the emotion (e.g., stress, anxiety, relaxation). The analysis results are stored on the server as emotional data.

[0362] Step 3:

[0363] The server uses a generative AI model based on the analyzed emotional data to generate content tailored to the user. In this step, emotional data is used as input, and individually optimized recommendation content is selected from a vast amount of content in the database. For example, music or videos that promote relaxation may be selected.

[0364] Step 4:

[0365] The server sends recommendation information for the generated content to the communication device. The communication device receives this information and presents it to the user. The presented content is fed back to the user visually or audibly, allowing the user to view or listen to content that matches their emotional state.

[0366] Step 5:

[0367] Users can view the presented content and, based on that experience, send feedback to the server via their communication device for future use. This feedback information is stored on the server and used for sentiment analysis and content generation in the future, thereby contributing to the provision of even more personalized experiences.

[0368] 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.

[0369] 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.

[0370] 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.

[0371] [Third Embodiment]

[0372] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0373] 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.

[0374] 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).

[0375] 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.

[0376] 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.

[0377] 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).

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] 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".

[0384] This invention is a system that provides legal advice using generative artificial intelligence, and its implementation requires multiple components. The system operates with a communication terminal and a server as its main components, providing an environment in which users can easily seek legal advice.

[0385] First, the user accesses the legal consultation system from their device. The communication device is connected to the internet and receives the consultation information entered by the user and transmits it to the server. The user can enter specific questions and situations related to legal issues.

[0386] Next, the server processes the received consultation request. Using artificial intelligence, the server generates optimal legal advice based on the input information. The AI ​​references the latest laws and precedents from legal databases to create advice tailored to the user's situation. This process is automated, enabling the provision of fast and accurate legal advice.

[0387] Once advice is generated, the server sends the results to the user via a communication terminal. At this point, the user can review the advice on the terminal and enter additional questions if necessary. Furthermore, if the user has a complex legal issue, the server can connect them with a human legal expert it has partnered with.

[0388] This system offers multiple pricing plans to enhance user convenience, with each plan providing a different level of service. This allows users to choose the plan that best suits their needs and budget. For example, the basic plan includes only AI-powered legal advice, while the advanced plan also allows consultation with human legal professionals.

[0389] For example, if a user wants advice regarding labor law, they input their work-related issues, and the server instantly generates legally compliant advice and sends it to their terminal. Based on this advice, the user can decide on their next steps. For instance, in more complex cases, the system may suggest the option of consulting with an expert.

[0390] By implementing these functions, users can quickly obtain necessary legal advice without being constrained by time or geographical limitations, and the system enables the efficient provision of legal consultations.

[0391] The following describes the processing flow.

[0392] Step 1:

[0393] The user accesses the legal consultation system using a communication device. They log in to the system by entering their username and password on the login screen displayed on the device.

[0394] Step 2:

[0395] The terminal displays a screen to the logged-in user, allowing them to select a legal consultation category (e.g., civil law, criminal law, labor law, etc.). The user chooses the area they wish to consult about and enters the details of their consultation into the text box.

[0396] Step 3:

[0397] The server receives the consultation content and selected category sent from the terminal. It then invokes a generating artificial intelligence to analyze the received content and extract the necessary legal knowledge.

[0398] Step 4:

[0399] The server uses artificial intelligence to generate optimal advice based on the input. The generation process references the latest legal information and relevant case precedents to create advice tailored to the user's specific needs.

[0400] Step 5:

[0401] The server sends the generated legal advice to the communication terminal. The terminal displays the results to the user and provides buttons for additional questions or confirmations.

[0402] Step 6:

[0403] The user reviews the advice and enters any further questions or concerns. This information is sent to the server via the device.

[0404] Step 7:

[0405] The server calls the AI ​​generator again based on the additional information and updates the advice. It then sends the newly generated advice to the terminal, providing feedback to the user.

[0406] Step 8:

[0407] If the situation is complex and requires more specialized assistance, the server will suggest connecting the user with a partner human legal expert. It will collect preferred meeting dates and details, and coordinate between the expert and the user.

[0408] Step 9:

[0409] When a user wants to select or change their pricing plan, they choose their desired plan from the list of plans displayed on their device and enter their payment information. This information is processed on the server, and the plan settings are updated.

[0410] (Example 1)

[0411] 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."

[0412] Traditional legal consultations primarily involved face-to-face meetings with experts, which presented problems such as time and location constraints and high costs. This resulted in a challenge for many people, making it difficult to obtain quick and convenient legal advice when needed.

[0413] 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.

[0414] In this invention, the server includes means for providing legal advice using generative artificial intelligence, means for receiving legal consultation information via an information processing device, and means for generating legal advice based on the received consultation information by referring to an information database. This enables users to obtain legal advice quickly and efficiently without being constrained by time or geographical limitations.

[0415] "Generative artificial intelligence" is a technology that generates new information based on input data and provides advice and solutions to specific problems.

[0416] An "information processing device" is a device that can receive, process, and transmit digital information, and plays a role in data communication between the user and the system.

[0417] "Consultation information" refers to specific data and questions that users provide to the system in order to resolve legal questions and problems.

[0418] An "information database" is a digital repository in which legal regulations, precedents, and other reference information are organized and stored, and is used as reference material for generating legal advice.

[0419] A "pricing menu" refers to a pricing structure designed to allow users to choose the plan that best suits them from multiple usage plans offered within the system.

[0420] This invention is implemented as a system that provides legal advice using generative artificial intelligence. The main components of the system are the user's terminal and the server. The user accesses the legal consultation system using their terminal and inputs specific legal consultation information. The terminal is connected to the internet and transmits this input information to the server. For example, the user can input a prompt such as, "Please tell me about the termination clause in the contract."

[0421] Next, the server processes the received consultation information. Specifically, the server is equipped with a generative AI model that analyzes the user's input. This analysis uses natural language processing technology to convert text information into a machine-understandable format. The server then searches for relevant laws and precedents by referring to a legal database and uses the generative AI model to generate optimal legal advice. This database contains a wide range of information on all aspects of law and serves as reference material necessary for generating advice.

[0422] The generated legal advice is sent from the server to the user's terminal, and the user can view the displayed advice. For example, if a user asks about "points to keep in mind when taking paid leave," the server uses its relevant legal database to create appropriate advice and provides it to the user via their terminal. The user can then decide on their next course of action based on this information and can enter further detailed questions if necessary.

[0423] This system enables a fast and efficient legal consultation and advice process, allowing users to access necessary information regardless of geographical constraints. To this end, multiple pricing options are available to suit individual user needs, and further support may be offered through the selection of the appropriate plan.

[0424] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0425] Step 1:

[0426] Users access the legal consultation system from their devices and input specific legal questions or situations. The prompts they enter might include phrases like "points to note when taking paid leave." This information is received by the device and formatted for transmission to the server. The output is the formatted data.

[0427] Step 2:

[0428] The terminal sends this formatted data to the server using a secure protocol. The data sent is text information containing specific details of the consultation. The output is data in a format that the server can receive.

[0429] Step 3:

[0430] The server receives data sent from the terminal. It takes the received data as input and first converts it into a format suitable for the generated AI model. This is done using natural language processing techniques. The output is data in a format that can be input into the AI ​​model.

[0431] Step 4:

[0432] The server searches the information database based on the converted data and collects relevant legal information. This search finds the latest laws and precedents. The output is highly relevant legal information.

[0433] Step 5:

[0434] The server uses a generative AI model to generate optimal legal advice based on collected legal information and in response to user input. A multi-layer neural network is used in this process. The output is the generated legal advice text.

[0435] Step 6:

[0436] The server sends the generated legal advice to the user's terminal. At this time, the output is formatted to a format viewable on the terminal. The output is formatted legal advice data for the user's terminal.

[0437] Step 7:

[0438] The terminal displays legal advice received from the server to the user. In the user interface, the advice is presented in a clear and organized format. The user uses this information to decide on their next course of action and enters additional questions if they require further details. The output is the legal advice information viewed by the user.

[0439] (Application Example 1)

[0440] 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."

[0441] With the increase in consumer transactions on online platforms, the legal issues consumers face are becoming more complex. However, there is a lack of quick and easy access to expert legal advice, making it difficult to properly address issues, particularly those related to returns and warranties.

[0442] 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.

[0443] In this invention, the server includes means for providing legal advice using generative artificial intelligence, means for identifying and providing advice on legal issues, and means for referencing information from legal databases related to an online platform. This enables consumers to obtain quick and accurate legal advice.

[0444] "Generative artificial intelligence" is an artificial system that has the ability to automatically generate legal advice based on the input content of the consultation.

[0445] A "communication device" is hardware or software that receives legal consultations from users via the internet and transmits them to a server.

[0446] "Means of generating legal advice" refers to the process of creating optimal legal advice by referencing information from legal databases based on the content of the consultation received.

[0447] A "legal database" is a collection of data containing the latest laws and precedents, and is a resource that generating AI refers to in order to provide appropriate advice.

[0448] "Means of identifying legal issues related to consumer transactions" refers to an analytical process for understanding the legal issues faced by users and providing specific legal advice.

[0449] To implement this invention, the user first accesses the legal consultation system using a communication terminal and inputs their consultation details. The terminal is connected to the internet and has the function of sending the user's inputted legal consultation to a server. The server is equipped with generating artificial intelligence and analyzes the received consultation details, referring to the latest laws and precedents contained in the legal database to identify legal issues related to delivery. Based on this, it generates appropriate legal advice and sends it to the user via the terminal. The server also has the ability to focus on specific legal issues related to consumer transactions and provide highly accurate advice on issues concerning returns and warranties.

[0450] This system uses Google Cloud's generative AI models to quickly and accurately generate advice by processing legal data. For example, when a user seeks advice regarding the return of a purchased item, the prompt might read: "I have an item I would like to return, but the refund conditions are unclear. Please tell me how I should legally handle the return and refund of this item." In this context, the generative AI model generates optimal advice, allowing the user to choose the appropriate course of action based on that advice.

[0451] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0452] Step 1:

[0453] The user accesses the legal consultation system using a communication terminal and enters specific details of their consultation. The entered data includes detailed information about the user's legal questions and problems. The terminal receives this input and prepares to send it to the server via the internet.

[0454] Step 2:

[0455] The server receives legal consultation details sent by the user. The received data includes the user's specific legal problem, and the server uses this data to prepare an access request to a legal database. The server analyzes and transforms the data, preparing it in a format that can be input into an AI model.

[0456] Step 3:

[0457] The server uses generative artificial intelligence to process the converted legal consultation content. The AI ​​references relevant laws and precedents from legal databases to generate the best advice for the user's legal problem. This data processing includes text analysis and the application of legal knowledge. The generated advice is then compiled into a new dataset.

[0458] Step 4:

[0459] The server sends the generated legal advice to the communication terminal. The terminal displays the requested advice to the user, who then reviews it to obtain information to decide on their next course of action. In this step, data transformation is performed to present the generated advice in a format that is easy for the user to understand.

[0460] 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.

[0461] This invention provides a system for conducting legal consultations efficiently and effectively, and by incorporating an emotion engine, it offers advice that takes into account the user's emotional state. The system mainly consists of a communication terminal, a server, a generative artificial intelligence, and an emotion engine.

[0462] First, the user accesses the legal consultation system using a communication terminal. At this time, the emotion engine analyzes the user's emotions from the input text and voice. The emotion engine determines the user's emotional state from their words and actions and the language they use, and sends this data to the server.

[0463] The server uses artificial intelligence to generate personalized advice based on received emotional data and legal consultation content. The tone and content of the advice are automatically adjusted to match the emotions recognized by the emotion engine. For example, if the user is feeling anxious, the consultation will include encouragement.

[0464] The generated advice is sent back to the communication terminal and provided to the user. The display format is customized to the user's emotional state, making it possible to design a UI that is visually and emotionally considerate.

[0465] Furthermore, if the emotion engine strongly indicates that the user is experiencing a specific emotional state (e.g., stress, tension), the server will suggest connecting the user with a human legal expert. The user will input their preferred date and time for the expert meeting and other details via their communication terminal, and the server will then coordinate the connection with the expert based on this information.

[0466] As a concrete example, consider a situation where a user is deeply troubled by a work-related issue. In this case, the emotion engine detects anxiety and impatience from the user's text. Based on this, the server can generate appropriate advice and suggest a consultation with a specialist as an option. This allows the user to gain a sense of security and receive support to take more appropriate action.

[0467] This system can significantly improve the legal consultation experience by recognizing the user's emotions and promptly providing appropriate legal advice and necessary support.

[0468] The following describes the processing flow.

[0469] Step 1:

[0470] The user accesses the legal consultation system using a communication device. They enter their username and password on the login screen and log in to the system.

[0471] Step 2:

[0472] The device displays a screen for selecting a legal consultation category. The user chooses the legal field they wish to consult about, enters their consultation details, and presses the submit button.

[0473] Step 3:

[0474] The terminal sends the user's input to the server for analysis. Simultaneously, the emotion engine performs emotion analysis based on the user's input.

[0475] Step 4:

[0476] The server retrieves the consultation content and emotional data received from the communication terminal. First, it checks the results analyzed by the emotion engine to understand the user's emotional state.

[0477] Step 5:

[0478] The server uses artificial intelligence to generate optimal legal advice based on the consultation content and emotional data. At this time, the tone and content of the advice are adjusted according to the emotional data.

[0479] Step 6:

[0480] The server sends the generated advice to the communication terminal. The terminal displays the legal advice tailored to the user.

[0481] Step 7:

[0482] The user reviews the advice and enters it again if they have additional questions or require further information. This causes the device to send the new information to the server.

[0483] Step 8:

[0484] Depending on the complexity of the situation and the user's emotional state, the server will suggest a meeting with a human legal expert. The user enters their preferred date and time and provides details for the connection.

[0485] Step 9:

[0486] Based on the user's request, the server coordinates schedules with affiliated legal professionals and confirms the meeting. The user participates in the meeting via a communication device.

[0487] (Example 2)

[0488] 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."

[0489] Traditional legal consultation systems often provide formal advice in response to the consultation content, and have the drawback of not being able to respond flexibly to the user's emotional state. Furthermore, even when the user is experiencing strong emotions, there is a problem in smoothly coordinating with experts.

[0490] 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.

[0491] In this invention, the server includes means for providing legal advice using a generation engine, means for receiving legal consultation content via an information processing device, and means incorporating an emotion engine for analyzing the user's emotions. This enables the rapid provision of accurate legal advice tailored to the user's emotional state, as well as smooth collaboration with legal professionals as needed.

[0492] A "generative engine" refers to software that uses a learning algorithm to generate legal advice based on input data.

[0493] An "information processing device" is a device used by users for communication, and includes hardware and software capable of receiving and processing legal consultation content.

[0494] An "emotion engine" is a function or program that analyzes the user's emotional state from their input, and is used to provide appropriate responses and adjustments based on that data.

[0495] A "legal expert" is a human professional with deep knowledge and experience in law, who can provide more specialized advice to users seeking assistance.

[0496] "Emotional data" refers to information indicating the emotional state, analyzed by the emotion engine from user input, and is used when adjusting the content and tone of legal advice.

[0497] "Adjusting the tone of advice" refers to the process of changing the tone and expression of legal advice provided to match the user's emotional state, in order to provide a more appropriate and empathetic response.

[0498] This invention is a system for providing advice that takes into account the emotional aspects when a user seeks legal advice. The system consists of an information processing device, a server, a generation engine, and an emotion engine.

[0499] The user first accesses the legal consultation system via an information processing device. This device is a standard computing device that communicates with the server via an internet connection. The user then inputs the specific details of their legal consultation in text or voice.

[0500] The communication terminal then sends this input to the emotion engine. The emotion engine uses text analysis and speech analysis techniques to identify the user's emotional state. The natural language processing techniques used analyze the user's word choice and tone of voice.

[0501] The server uses a generative engine based on received sentiment data to generate legal advice. The generative engine employs a generative AI model that has been pre-trained with legal data. The tone and content of the generated legal advice are adjusted according to the data from the sentiment engine. For example, if the user is feeling stressed, the advice will be generated in a more reassuring tone.

[0502] The generated advice is sent back to the communication terminal and presented to the user. At this point, the advice is displayed visually through a user interface customized according to the user's emotional state. In particular, designs aimed at alleviating tension are sometimes employed.

[0503] For example, if a user seeks advice about anxieties related to work issues, the emotion engine may recognize the anxious feelings, and the generation engine may generate advice such as, "Don't worry. This problem is solvable. There are several options."

[0504] An example of a prompt message might be something like, "A system using a generation engine to provide emotionally sensitive legal advice to users who are anxious about labor issues." This would enable appropriate and emotionally sensitive legal support.

[0505] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0506] Step 1:

[0507] Users access the legal consultation system using an information processing device and input their consultation details in text or voice. The data entered consists of the user's specific legal questions and descriptions of their situation. This constitutes the input for this process.

[0508] Step 2:

[0509] The communication terminal receives input from the user and sends it to the emotion engine. The emotion engine analyzes emotions from the input text or speech using natural language processing. Specifically, it identifies emotional states (e.g., anxiety, relief, anger). The result of this analysis becomes the output.

[0510] Step 3:

[0511] The server receives the analysis results from the emotion engine and uses the generation engine to generate legal advice. The input consists of the analyzed emotion data and the user's consultation content. The generation engine applies a learned algorithm using this data to create appropriate legal advice. The output is adjusted advice that takes the user's feelings into consideration.

[0512] Step 4:

[0513] The server then sends the generated advice back to the communication terminal. This transmission process is performed to present the advice to the user at an appropriate time. The output is customized advice tailored to the user's emotions.

[0514] Step 5:

[0515] The communication terminal displays advice sent from the server to the user. Specifically, it displays the advice on the user's device using a visually appealing interface. The output is presented in a user-friendly format, with the font size and color adjusted according to the user's emotional state.

[0516] Step 6:

[0517] If the emotion engine determines that the user's emotional state is particularly serious, the server will suggest connecting the user with a human legal expert. The user will specify preferred meeting dates and times, and this information will be used to coordinate with the expert. The output will include the specific date and time of the consultation and the progress of the consultation arrangement.

[0518] (Application Example 2)

[0519] 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."

[0520] This invention addresses the challenge of enabling personalized content recommendations in online content delivery that take into account the emotional state of users. Modern digital content delivery platforms are required to appropriately understand users' emotions and psychological states and provide appropriate content accordingly, but there is a problem in that no system adequately meets this need.

[0521] 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.

[0522] In this invention, the server includes means for determining the user's emotional state based on emotion analysis, means for adjusting the generated advice according to the emotional state, and means for providing recommendation information based on the emotional state. This makes it possible to automatically generate content appropriate to each user's emotions and improve the user experience.

[0523] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to autonomously make judgments and generate appropriate advice and recommendations based on user input information.

[0524] A "communication device" is a device that has the function of receiving information from users and transmitting output from the system to users.

[0525] "Emotional analysis" is a technology that determines and classifies a user's emotional state based on their input information. It is a process of understanding a user's psychological state by analyzing text and audio information.

[0526] "Emotional state" refers to information that indicates the user's psychological or emotional condition, and is expressed as a result of analysis by the system.

[0527] "Providing recommendations" refers to the act of suggesting personalized content and services based on the user's emotional state.

[0528] This invention is a system for realizing personalized content delivery based on the emotional state of users. The system mainly consists of a server and a communication device, and uses emotion analysis and generative AI models.

[0529] The server receives input data from the communication device. This data includes consultation content in text and audio formats. The server uses emotion analysis technology to determine the user's emotional state from this data. Specifically, it quickly extracts the user's emotional state through emotion recognition software. The results of the emotion recognition are processed within the server and stored as emotion data.

[0530] Next, the server utilizes a generative AI model to generate content tailored to the user's emotional state. This generation process selects appropriate information from a vast content database and presents it in the format best suited to the user. For example, if the system determines that the user wants to relax, it will recommend calming music or images of natural scenery.

[0531] The communication device presents the user with recommendation information sent from the server. This allows the user to seamlessly obtain content that suits their emotional state. For example, if a user inputs a voice message saying, "It was a stressful day," the system will recommend relaxation music or videos for viewing.

[0532] An example of a prompt from the generating AI model is: "Identify the emotion from the user's voice statement, 'It was a stressful day,' and recommend relaxation music or movies appropriate for that emotion." In this way, this system enables the recommendation of high-value content based on the user's emotions.

[0533] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0534] Step 1:

[0535] The user provides input information (e.g., text or voice) that influences their emotions through a communication device. The communication device sends this input data to the server. The input data contains information that indicates the user's emotional state.

[0536] Step 2:

[0537] The server uses emotion recognition software to analyze the received input data and identify the user's emotional state. This process extracts keywords and tones from the input data, and based on these, classifies the emotion (e.g., stress, anxiety, relaxation). The analysis results are stored on the server as emotional data.

[0538] Step 3:

[0539] The server uses a generative AI model based on the analyzed emotional data to generate content tailored to the user. In this step, emotional data is used as input, and individually optimized recommendation content is selected from a vast amount of content in the database. For example, music or videos that promote relaxation may be selected.

[0540] Step 4:

[0541] The server sends recommendation information for the generated content to the communication device. The communication device receives this information and presents it to the user. The presented content is fed back to the user visually or audibly, allowing the user to view or listen to content that matches their emotional state.

[0542] Step 5:

[0543] Users can view the presented content and, based on that experience, send feedback to the server via their communication device for future use. This feedback information is stored on the server and used for sentiment analysis and content generation in the future, thereby contributing to the provision of even more personalized experiences.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] [Fourth Embodiment]

[0548] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0549] 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.

[0550] 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).

[0551] 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.

[0552] 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.

[0553] 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).

[0554] 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.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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".

[0561] This invention is a system that provides legal advice using generative artificial intelligence, and its implementation requires multiple components. The system operates with a communication terminal and a server as its main components, providing an environment in which users can easily seek legal advice.

[0562] First, the user accesses the legal consultation system from their device. The communication device is connected to the internet and receives the consultation information entered by the user and transmits it to the server. The user can enter specific questions and situations related to legal issues.

[0563] Next, the server processes the received consultation request. Using artificial intelligence, the server generates optimal legal advice based on the input information. The AI ​​references the latest laws and precedents from legal databases to create advice tailored to the user's situation. This process is automated, enabling the provision of fast and accurate legal advice.

[0564] Once advice is generated, the server sends the results to the user via a communication terminal. At this point, the user can review the advice on the terminal and enter additional questions if necessary. Furthermore, if the user has a complex legal issue, the server can connect them with a human legal expert it has partnered with.

[0565] This system offers multiple pricing plans to enhance user convenience, with each plan providing a different level of service. This allows users to choose the plan that best suits their needs and budget. For example, the basic plan includes only AI-powered legal advice, while the advanced plan also allows consultation with human legal professionals.

[0566] For example, if a user wants advice regarding labor law, they input their work-related issues, and the server instantly generates legally compliant advice and sends it to their terminal. Based on this advice, the user can decide on their next steps. For instance, in more complex cases, the system may suggest the option of consulting with an expert.

[0567] By implementing these functions, users can quickly obtain necessary legal advice without being constrained by time or geographical limitations, and the system enables the efficient provision of legal consultations.

[0568] The following describes the processing flow.

[0569] Step 1:

[0570] The user accesses the legal consultation system using a communication device. They log in to the system by entering their username and password on the login screen displayed on the device.

[0571] Step 2:

[0572] The terminal displays a screen to the logged-in user, allowing them to select a legal consultation category (e.g., civil law, criminal law, labor law, etc.). The user chooses the area they wish to consult about and enters the details of their consultation into the text box.

[0573] Step 3:

[0574] The server receives the consultation content and selected category sent from the terminal. It then invokes a generating artificial intelligence to analyze the received content and extract the necessary legal knowledge.

[0575] Step 4:

[0576] The server uses artificial intelligence to generate optimal advice based on the input. The generation process references the latest legal information and relevant case precedents to create advice tailored to the user's specific needs.

[0577] Step 5:

[0578] The server sends the generated legal advice to the communication terminal. The terminal displays the results to the user and provides buttons for additional questions or confirmations.

[0579] Step 6:

[0580] The user reviews the advice and enters any further questions or concerns. This information is sent to the server via the device.

[0581] Step 7:

[0582] The server calls the AI ​​generator again based on the additional information and updates the advice. It then sends the newly generated advice to the terminal, providing feedback to the user.

[0583] Step 8:

[0584] If the situation is complex and requires more specialized assistance, the server will suggest connecting the user with a partner human legal expert. It will collect preferred meeting dates and details, and coordinate between the expert and the user.

[0585] Step 9:

[0586] When a user wants to select or change their pricing plan, they choose their desired plan from the list of plans displayed on their device and enter their payment information. This information is processed on the server, and the plan settings are updated.

[0587] (Example 1)

[0588] 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".

[0589] Traditional legal consultations primarily involved face-to-face meetings with experts, which presented problems such as time and location constraints and high costs. This resulted in a challenge for many people, making it difficult to obtain quick and convenient legal advice when needed.

[0590] 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.

[0591] In this invention, the server includes means for providing legal advice using generative artificial intelligence, means for receiving legal consultation information via an information processing device, and means for generating legal advice based on the received consultation information by referring to an information database. This enables users to obtain legal advice quickly and efficiently without being constrained by time or geographical limitations.

[0592] "Generative artificial intelligence" is a technology that generates new information based on input data and provides advice and solutions to specific problems.

[0593] An "information processing device" is a device that can receive, process, and transmit digital information, and plays a role in data communication between the user and the system.

[0594] "Consultation information" refers to specific data and questions that users provide to the system in order to resolve legal questions and problems.

[0595] An "information database" is a digital repository in which legal regulations, precedents, and other reference information are organized and stored, and is used as reference material for generating legal advice.

[0596] A "pricing menu" refers to a pricing structure designed to allow users to choose the plan that best suits them from multiple usage plans offered within the system.

[0597] This invention is implemented as a system that provides legal advice using generative artificial intelligence. The main components of the system are the user's terminal and the server. The user accesses the legal consultation system using their terminal and inputs specific legal consultation information. The terminal is connected to the internet and transmits this input information to the server. For example, the user can input a prompt such as, "Please tell me about the termination clause in the contract."

[0598] Next, the server processes the received consultation information. Specifically, the server is equipped with a generative AI model that analyzes the user's input. This analysis uses natural language processing technology to convert text information into a machine-understandable format. The server then searches for relevant laws and precedents by referring to a legal database and uses the generative AI model to generate optimal legal advice. This database contains a wide range of information on all aspects of law and serves as reference material necessary for generating advice.

[0599] The generated legal advice is sent from the server to the user's terminal, and the user can view the displayed advice. For example, if a user asks about "points to keep in mind when taking paid leave," the server uses its relevant legal database to create appropriate advice and provides it to the user via their terminal. The user can then decide on their next course of action based on this information and can enter further detailed questions if necessary.

[0600] This system enables a fast and efficient legal consultation and advice process, allowing users to access necessary information regardless of geographical constraints. To this end, multiple pricing options are available to suit individual user needs, and further support may be offered through the selection of the appropriate plan.

[0601] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0602] Step 1:

[0603] Users access the legal consultation system from their devices and input specific legal questions or situations. The prompts they enter might include phrases like "points to note when taking paid leave." This information is received by the device and formatted for transmission to the server. The output is the formatted data.

[0604] Step 2:

[0605] The terminal sends this formatted data to the server using a secure protocol. The data sent is text information containing specific details of the consultation. The output is data in a format that the server can receive.

[0606] Step 3:

[0607] The server receives data sent from the terminal. It takes the received data as input and first converts it into a format suitable for the generated AI model. This is done using natural language processing techniques. The output is data in a format that can be input into the AI ​​model.

[0608] Step 4:

[0609] The server searches the information database based on the converted data and collects relevant legal information. This search finds the latest laws and precedents. The output is highly relevant legal information.

[0610] Step 5:

[0611] The server uses a generative AI model to generate optimal legal advice based on collected legal information and in response to user input. A multi-layer neural network is used in this process. The output is the generated legal advice text.

[0612] Step 6:

[0613] The server sends the generated legal advice to the user's terminal. At this time, the output is formatted to a format viewable on the terminal. The output is formatted legal advice data for the user's terminal.

[0614] Step 7:

[0615] The terminal displays legal advice received from the server to the user. In the user interface, the advice is presented in a clear and organized format. The user uses this information to decide on their next course of action and enters additional questions if they require further details. The output is the legal advice information viewed by the user.

[0616] (Application Example 1)

[0617] 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".

[0618] With the increase in consumer transactions on online platforms, the legal issues consumers face are becoming more complex. However, there is a lack of quick and easy access to expert legal advice, making it difficult to properly address issues, particularly those related to returns and warranties.

[0619] 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.

[0620] In this invention, the server includes means for providing legal advice using generative artificial intelligence, means for identifying and providing advice on legal issues, and means for referencing information from legal databases related to an online platform. This enables consumers to obtain quick and accurate legal advice.

[0621] "Generative artificial intelligence" is an artificial system that has the ability to automatically generate legal advice based on the input content of the consultation.

[0622] A "communication device" is hardware or software that receives legal consultations from users via the internet and transmits them to a server.

[0623] "Means of generating legal advice" refers to the process of creating optimal legal advice by referencing information from legal databases based on the content of the consultation received.

[0624] A "legal database" is a collection of data containing the latest laws and precedents, and is a resource that generating AI refers to in order to provide appropriate advice.

[0625] "Means of identifying legal issues related to consumer transactions" refers to an analytical process for understanding the legal issues faced by users and providing specific legal advice.

[0626] To implement this invention, the user first accesses the legal consultation system using a communication terminal and inputs their consultation details. The terminal is connected to the internet and has the function of sending the user's inputted legal consultation to a server. The server is equipped with generating artificial intelligence and analyzes the received consultation details, referring to the latest laws and precedents contained in the legal database to identify legal issues related to delivery. Based on this, it generates appropriate legal advice and sends it to the user via the terminal. The server also has the ability to focus on specific legal issues related to consumer transactions and provide highly accurate advice on issues concerning returns and warranties.

[0627] This system uses Google Cloud's generative AI models to quickly and accurately generate advice by processing legal data. For example, when a user seeks advice regarding the return of a purchased item, the prompt might read: "I have an item I would like to return, but the refund conditions are unclear. Please tell me how I should legally handle the return and refund of this item." In this context, the generative AI model generates optimal advice, allowing the user to choose the appropriate course of action based on that advice.

[0628] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0629] Step 1:

[0630] The user accesses the legal consultation system using a communication terminal and enters specific details of their consultation. The entered data includes detailed information about the user's legal questions and problems. The terminal receives this input and prepares to send it to the server via the internet.

[0631] Step 2:

[0632] The server receives legal consultation details sent by the user. The received data includes the user's specific legal problem, and the server uses this data to prepare an access request to a legal database. The server analyzes and transforms the data, preparing it in a format that can be input into an AI model.

[0633] Step 3:

[0634] The server uses generative artificial intelligence to process the converted legal consultation content. The AI ​​references relevant laws and precedents from legal databases to generate the best advice for the user's legal problem. This data processing includes text analysis and the application of legal knowledge. The generated advice is then compiled into a new dataset.

[0635] Step 4:

[0636] The server sends the generated legal advice to the communication terminal. The terminal displays the requested advice to the user, who then reviews it to obtain information to decide on their next course of action. In this step, data transformation is performed to present the generated advice in a format that is easy for the user to understand.

[0637] 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.

[0638] This invention provides a system for conducting legal consultations efficiently and effectively, and by incorporating an emotion engine, it offers advice that takes into account the user's emotional state. The system mainly consists of a communication terminal, a server, a generative artificial intelligence, and an emotion engine.

[0639] First, the user accesses the legal consultation system using a communication terminal. At this time, the emotion engine analyzes the user's emotions from the input text and voice. The emotion engine determines the user's emotional state from their words and actions and the language they use, and sends this data to the server.

[0640] The server uses artificial intelligence to generate personalized advice based on received emotional data and legal consultation content. The tone and content of the advice are automatically adjusted to match the emotions recognized by the emotion engine. For example, if the user is feeling anxious, the consultation will include encouragement.

[0641] The generated advice is sent back to the communication terminal and provided to the user. The display format is customized to the user's emotional state, making it possible to design a UI that is visually and emotionally considerate.

[0642] Furthermore, if the emotion engine strongly indicates that the user is experiencing a specific emotional state (e.g., stress, tension), the server will suggest connecting the user with a human legal expert. The user will input their preferred date and time for the expert meeting and other details via their communication terminal, and the server will then coordinate the connection with the expert based on this information.

[0643] As a concrete example, consider a situation where a user is deeply troubled by a work-related issue. In this case, the emotion engine detects anxiety and impatience from the user's text. Based on this, the server can generate appropriate advice and suggest a consultation with a specialist as an option. This allows the user to gain a sense of security and receive support to take more appropriate action.

[0644] This system can significantly improve the legal consultation experience by recognizing the user's emotions and promptly providing appropriate legal advice and necessary support.

[0645] The following describes the processing flow.

[0646] Step 1:

[0647] The user accesses the legal consultation system using a communication device. They enter their username and password on the login screen and log in to the system.

[0648] Step 2:

[0649] The device displays a screen for selecting a legal consultation category. The user chooses the legal field they wish to consult about, enters their consultation details, and presses the submit button.

[0650] Step 3:

[0651] The terminal sends the user's input to the server for analysis. Simultaneously, the emotion engine performs emotion analysis based on the user's input.

[0652] Step 4:

[0653] The server retrieves the consultation content and emotional data received from the communication terminal. First, it checks the results analyzed by the emotion engine to understand the user's emotional state.

[0654] Step 5:

[0655] The server uses artificial intelligence to generate optimal legal advice based on the consultation content and emotional data. At this time, the tone and content of the advice are adjusted according to the emotional data.

[0656] Step 6:

[0657] The server sends the generated advice to the communication terminal. The terminal displays the legal advice tailored to the user.

[0658] Step 7:

[0659] The user reviews the advice and enters it again if they have additional questions or require further information. This causes the device to send the new information to the server.

[0660] Step 8:

[0661] Depending on the complexity of the situation and the user's emotional state, the server will suggest a meeting with a human legal expert. The user enters their preferred date and time and provides details for the connection.

[0662] Step 9:

[0663] Based on the user's request, the server coordinates schedules with affiliated legal professionals and confirms the meeting. The user participates in the meeting via a communication device.

[0664] (Example 2)

[0665] 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".

[0666] Traditional legal consultation systems often provide formal advice in response to the consultation content, and have the drawback of not being able to respond flexibly to the user's emotional state. Furthermore, even when the user is experiencing strong emotions, there is a problem in smoothly coordinating with experts.

[0667] 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.

[0668] In this invention, the server includes means for providing legal advice using a generation engine, means for receiving legal consultation content via an information processing device, and means incorporating an emotion engine for analyzing the user's emotions. This enables the rapid provision of accurate legal advice tailored to the user's emotional state, as well as smooth collaboration with legal professionals as needed.

[0669] A "generative engine" refers to software that uses a learning algorithm to generate legal advice based on input data.

[0670] An "information processing device" is a device used by users for communication, and includes hardware and software capable of receiving and processing legal consultation content.

[0671] An "emotion engine" is a function or program that analyzes the user's emotional state from their input, and is used to provide appropriate responses and adjustments based on that data.

[0672] A "legal expert" is a human professional with deep knowledge and experience in law, who can provide more specialized advice to users seeking assistance.

[0673] "Emotional data" refers to information indicating the emotional state, analyzed by the emotion engine from user input, and is used when adjusting the content and tone of legal advice.

[0674] "Adjusting the tone of advice" refers to the process of changing the tone and expression of legal advice provided to match the user's emotional state, in order to provide a more appropriate and empathetic response.

[0675] This invention is a system for providing advice that takes into account the emotional aspects when a user seeks legal advice. The system consists of an information processing device, a server, a generation engine, and an emotion engine.

[0676] The user first accesses the legal consultation system via an information processing device. This device is a standard computing device that communicates with the server via an internet connection. The user then inputs the specific details of their legal consultation in text or voice.

[0677] The communication terminal then sends this input to the emotion engine. The emotion engine uses text analysis and speech analysis techniques to identify the user's emotional state. The natural language processing techniques used analyze the user's word choice and tone of voice.

[0678] The server uses a generative engine based on received sentiment data to generate legal advice. The generative engine employs a generative AI model that has been pre-trained with legal data. The tone and content of the generated legal advice are adjusted according to the data from the sentiment engine. For example, if the user is feeling stressed, the advice will be generated in a more reassuring tone.

[0679] The generated advice is sent back to the communication terminal and presented to the user. At this point, the advice is displayed visually through a user interface customized according to the user's emotional state. In particular, designs aimed at alleviating tension are sometimes employed.

[0680] For example, if a user seeks advice about anxieties related to work issues, the emotion engine may recognize the anxious feelings, and the generation engine may generate advice such as, "Don't worry. This problem is solvable. There are several options."

[0681] An example of a prompt message might be something like, "A system using a generation engine to provide emotionally sensitive legal advice to users who are anxious about labor issues." This would enable appropriate and emotionally sensitive legal support.

[0682] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0683] Step 1:

[0684] Users access the legal consultation system using an information processing device and input their consultation details in text or voice. The data entered consists of the user's specific legal questions and descriptions of their situation. This constitutes the input for this process.

[0685] Step 2:

[0686] The communication terminal receives input from the user and sends it to the emotion engine. The emotion engine analyzes emotions from the input text or speech using natural language processing. Specifically, it identifies emotional states (e.g., anxiety, relief, anger). The result of this analysis becomes the output.

[0687] Step 3:

[0688] The server receives the analysis results from the emotion engine and uses the generation engine to generate legal advice. The input consists of the analyzed emotion data and the user's consultation content. The generation engine applies a learned algorithm using this data to create appropriate legal advice. The output is adjusted advice that takes the user's feelings into consideration.

[0689] Step 4:

[0690] The server then sends the generated advice back to the communication terminal. This transmission process is performed to present the advice to the user at an appropriate time. The output is customized advice tailored to the user's emotions.

[0691] Step 5:

[0692] The communication terminal displays advice sent from the server to the user. Specifically, it displays the advice on the user's device using a visually appealing interface. The output is presented in a user-friendly format, with the font size and color adjusted according to the user's emotional state.

[0693] Step 6:

[0694] If the emotion engine determines that the user's emotional state is particularly serious, the server will suggest connecting the user with a human legal expert. The user will specify preferred meeting dates and times, and this information will be used to coordinate with the expert. The output will include the specific date and time of the consultation and the progress of the consultation arrangement.

[0695] (Application Example 2)

[0696] 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".

[0697] This invention addresses the challenge of enabling personalized content recommendations in online content delivery that take into account the emotional state of users. Modern digital content delivery platforms are required to appropriately understand users' emotions and psychological states and provide appropriate content accordingly, but there is a problem in that no system adequately meets this need.

[0698] 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.

[0699] In this invention, the server includes means for determining the user's emotional state based on emotion analysis, means for adjusting the generated advice according to the emotional state, and means for providing recommendation information based on the emotional state. This makes it possible to automatically generate content appropriate to each user's emotions and improve the user experience.

[0700] "Generative artificial intelligence" is an artificial intelligence technology that has the ability to autonomously make judgments and generate appropriate advice and recommendations based on user input information.

[0701] A "communication device" is a device that has the function of receiving information from users and transmitting output from the system to users.

[0702] "Emotional analysis" is a technology that determines and classifies a user's emotional state based on their input information. It is a process of understanding a user's psychological state by analyzing text and audio information.

[0703] "Emotional state" refers to information that indicates the user's psychological or emotional condition, and is expressed as a result of analysis by the system.

[0704] "Providing recommendations" refers to the act of suggesting personalized content and services based on the user's emotional state.

[0705] This invention is a system for realizing personalized content delivery based on the emotional state of users. The system mainly consists of a server and a communication device, and uses emotion analysis and generative AI models.

[0706] The server receives input data from the communication device. This data includes consultation content in text and audio formats. The server uses emotion analysis technology to determine the user's emotional state from this data. Specifically, it quickly extracts the user's emotional state through emotion recognition software. The results of the emotion recognition are processed within the server and stored as emotion data.

[0707] Next, the server utilizes a generative AI model to generate content tailored to the user's emotional state. This generation process selects appropriate information from a vast content database and presents it in the format best suited to the user. For example, if the system determines that the user wants to relax, it will recommend calming music or images of natural scenery.

[0708] The communication device presents the user with recommendation information sent from the server. This allows the user to seamlessly obtain content that suits their emotional state. For example, if a user inputs a voice message saying, "It was a stressful day," the system will recommend relaxation music or videos for viewing.

[0709] An example of a prompt from the generating AI model is: "Identify the emotion from the user's voice statement, 'It was a stressful day,' and recommend relaxation music or movies appropriate for that emotion." In this way, this system enables the recommendation of high-value content based on the user's emotions.

[0710] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0711] Step 1:

[0712] The user provides input information (e.g., text or voice) that influences their emotions through a communication device. The communication device sends this input data to the server. The input data contains information that indicates the user's emotional state.

[0713] Step 2:

[0714] The server uses emotion recognition software to analyze the received input data and identify the user's emotional state. This process extracts keywords and tones from the input data, and based on these, classifies the emotion (e.g., stress, anxiety, relaxation). The analysis results are stored on the server as emotional data.

[0715] Step 3:

[0716] The server uses a generative AI model based on the analyzed emotional data to generate content tailored to the user. In this step, emotional data is used as input, and individually optimized recommendation content is selected from a vast amount of content in the database. For example, music or videos that promote relaxation may be selected.

[0717] Step 4:

[0718] The server sends recommendation information for the generated content to the communication device. The communication device receives this information and presents it to the user. The presented content is fed back to the user visually or audibly, allowing the user to view or listen to content that matches their emotional state.

[0719] Step 5:

[0720] Users can view the presented content and, based on that experience, send feedback to the server via their communication device for future use. This feedback information is stored on the server and used for sentiment analysis and content generation in the future, thereby contributing to the provision of even more personalized experiences.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0728] 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.

[0729] 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."

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] The following is further disclosed regarding the embodiments described above.

[0743] (Claim 1)

[0744] A means of providing legal advice using generative artificial intelligence,

[0745] A means of receiving legal consultations via a communication terminal,

[0746] A means of generating legal advice based on the content of the consultation received,

[0747] Means for transmitting generated legal advice,

[0748] A system that includes this.

[0749] (Claim 2)

[0750] The system according to claim 1, further comprising means for establishing a connection with a human legal expert in response to a request from a communication terminal.

[0751] (Claim 3)

[0752] The system according to claim 1, further comprising means for managing multiple pricing plans based on user selection.

[0753] "Example 1"

[0754] (Claim 1)

[0755] A means of providing legal advice using generative artificial intelligence,

[0756] A means of receiving legal consultation information via an information processing device,

[0757] A means of generating legal advice by referring to an information database based on the consultation information received,

[0758] A means for transmitting the generated legal advice to an information processing device,

[0759] A means for displaying the generated advice on an information processing device,

[0760] A system that includes this.

[0761] (Claim 2)

[0762] The system according to claim 1, further comprising means for establishing a connection with a human legal expert in response to a request from an information processing device.

[0763] (Claim 3)

[0764] The system according to claim 1, further comprising means for managing multiple pricing menus based on user selection.

[0765] "Application Example 1"

[0766] (Claim 1)

[0767] A means of providing legal advice using generative artificial intelligence,

[0768] A means of receiving legal consultations via a communication device,

[0769] A means of generating legal advice based on the content of the consultation received,

[0770] Means for transmitting generated legal advice,

[0771] Means for identifying and providing advice on legal issues related to consumer transactions,

[0772] Means of accessing information from legal databases related to online platforms,

[0773] A system that includes this.

[0774] (Claim 2)

[0775] The system according to claim 1, further comprising means for establishing a connection with a human legal expert in response to a request from a communication device.

[0776] (Claim 3)

[0777] The system according to claim 1, further comprising means for managing multiple pricing plans based on user selection.

[0778] "Example 2 of combining an emotion engine"

[0779] (Claim 1)

[0780] A means of providing legal advice using a generation engine,

[0781] A means of receiving legal consultation content via an information processing device,

[0782] A means of generating legal advice based on the content of the consultation received,

[0783] A method incorporating an emotion engine that analyzes the user's emotions,

[0784] A means of adjusting the tone of advice based on analyzed emotional data,

[0785] Means for sending generated legal advice,

[0786] A system that includes this.

[0787] (Claim 2)

[0788] The system according to claim 1, further comprising means for establishing a connection with a legal expert in response to a request from the processing device.

[0789] (Claim 3)

[0790] The system according to claim 1, further comprising means for managing multiple pricing plans based on user selection.

[0791] "Application example 2 when combining with an emotional engine"

[0792] (Claim 1)

[0793] A means of providing advice on knowledge using generative artificial intelligence,

[0794] A means of receiving inquiries about knowledge via a communication device,

[0795] A means of generating knowledge-related advice based on the content of the consultation received,

[0796] Means for transmitting advice regarding generated knowledge,

[0797] A means of determining the emotional state of a user based on emotion analysis,

[0798] A means of adjusting the generated advice according to the emotional state,

[0799] A means of providing recommendation information based on emotional state,

[0800] A system that includes this.

[0801] (Claim 2)

[0802] The system according to claim 1, further comprising means for establishing a connection with a human expert in response to a request from a communication device.

[0803] (Claim 3)

[0804] The system according to claim 1, further comprising means for managing multiple pricing plans based on user selection. [Explanation of Symbols]

[0805] 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 providing legal advice using generative artificial intelligence, A means of receiving legal consultations via a communication terminal, A means of generating legal advice based on the content of the consultation received, Means for transmitting generated legal advice, A system that includes this.

2. The system according to claim 1, further comprising means for establishing a connection with a human legal expert in response to a request from a communication terminal.

3. The system according to claim 1, further comprising means for managing multiple pricing plans based on user selection.

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