system

Abstract

We provide the system. [Solution] A means of receiving and classifying income information entered by users, A means of generating the necessary tax documents based on classified income information, A means for analyzing the entered expense information, identifying and calculating related expense items, Means of providing users with tax information and calculation results, A means for receiving questions from users and generating answers using natural language processing technology, A means of notifying users of necessary documents and procedures, 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 the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] [There is a need for a system that can reduce the complexity of the final tax return procedures faced by individuals and business owners, the time burden, and the occurrence of mistakes, and can perform accurate tax processing efficiently. This problem is particularly serious for freelancers and business owners with multiple income sources, and means that can flexibly respond to changes in the tax system are required.]

Means for Solving the Problems

[0005] [This invention provides a system that receives income information entered by a user, classifies it appropriately, and automates the generation of tax documents based on this information. Furthermore, it includes means for analyzing entered expense information to identify relevant expense items and perform accurate calculations. In addition, it provides rapid answers to user questions using natural language processing and notifies users of necessary submission reminders in real time, thereby seamlessly supporting the entire process.]

[0006] A "user" refers to a person who uses the system to input income and expense information and perform tax processing.

[0007] "Income information" refers to data about the income earned by the user, and includes various types of income data such as salary income and income from side jobs.

[0008] "Means of classification" refers to the processes and system functions for dividing and organizing input income information according to its type and characteristics.

[0009] "Tax documents" are official documents required for filing income tax and other tax returns, and are generated for submission to the tax authorities.

[0010] "Expense information" refers to data relating to expenditures incurred for business activities or other purposes, including those that may be deductible.

[0011] "Means of analysis" refers to methods or techniques for analyzing input data in detail and understanding its meaning and relationships.

[0012] "Natural language processing" refers to the technology that enables computers to understand and process human language, and is used to generate meaningful responses to questions.

[0013] A "reminder" is information that users are notified of to remind them of a specific action or submission deadline, and it functions as a way to alert them. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

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

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

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

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

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

[0022] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0035] This invention provides a system that enables users to efficiently complete their tax return procedures. This system processes income and expense information entered from the user's terminal on a server, enabling the generation of necessary tax documents and real-time responses to inquiries.

[0036] The server first receives income information submitted by the user and categorizes it appropriately. For example, the server distinguishes between salary income and real estate income, and stores it in the database in a predetermined format as needed. This eliminates the need for users to manually categorize the information, significantly reducing the effort required for data entry.

[0037] Next, regarding expense information, the server receives images of receipts and invoices uploaded by the user from their device and analyzes their contents using an AI model. The server identifies expense items and automatically calculates the totals. For example, business-related transportation and communication expenses are detected and aggregated as legitimate expenses.

[0038] Users can input any questions that arise during the tax filing process into their terminals. The server uses natural language processing to analyze the user's questions and generates appropriate answers by referring to relevant tax laws and historical database information. This response is provided to the user in real time, allowing them to immediately resolve any anxieties or questions they may have during the process.

[0039] Furthermore, the server has a function that automatically generates reminders and notifies the user's device when the filing deadline or the deadline for submitting necessary documents is approaching. This allows users to complete the process smoothly without forgetting important deadlines.

[0040] As described above, this system assists users in the tax filing process by simplifying complex tax procedures and providing necessary information in a timely manner.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users enter income information via their device and send it to the server. Users enter their salary income and other sources of income into a dedicated form. They can select the type of income using dropdown menus or checkboxes.

[0044] Step 2:

[0045] The server processes income information received from users and classifies it into appropriate categories. Based on rules set within the server, the information is categorized into salary income, real estate income, business income, etc., and registered in the database.

[0046] Step 3:

[0047] Users enter expense information into their terminal and upload images of relevant receipts to the server. They enter the type and amount of the expense into a form and attach photos of the receipts.

[0048] Step 4:

[0049] The server analyzes the uploaded receipt image and automatically extracts expense items using AI technology. An image processing algorithm recognizes the text, automatically classifies it into categories such as transportation expenses and communication expenses, and performs calculations.

[0050] Step 5:

[0051] The server generates the necessary tax documents based on aggregated income and expense information. It creates the documents in the latest format corresponding to the tax year and generates files for user review.

[0052] Step 6:

[0053] Users can input questions about their tax return process from their terminal. If they have a question, they enter it in the text form and send it to the server.

[0054] Step 7:

[0055] The server uses natural language processing to analyze the user's question and generate an appropriate answer. It refers to relevant laws and historical data to generate the answer text and send it back to the terminal.

[0056] Step 8:

[0057] The server sets reminders for important deadlines and sends notifications to the user's device as the submission deadline approaches. Based on the reminder settings, it also sends push notifications and emails to alert users.

[0058] This series of processes allows users to efficiently handle complex tax procedures and receive necessary information and support in real time.

[0059] (Example 1)

[0060] 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."

[0061] Traditional tax procedures require users to manually input and categorize their income and expense information, which is time-consuming and laborious. Furthermore, there is no means to quickly obtain answers to questions, and there is a risk of forgetting to submit the appropriate documents on time. Additionally, if the generated document formats are incompatible, delays in the process can occur.

[0062] 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.

[0063] In this invention, the server includes means for receiving and classifying income information entered by the user, means for analyzing entered expense information, identifying and calculating related expense items, and means for receiving questions from the user and generating answers using natural language processing technology. This enables the user to efficiently manage income and expense information, quickly resolve questions, and submit accurate documents within the appropriate timeframe.

[0064] A "user" refers to a person who uses the system to input income and expense information and receives the processing results.

[0065] "Income information" refers to data related to monetary receipts, such as salaries and business income.

[0066] "Expense information" refers to data related to expenditures incurred in the course of business operations.

[0067] "Classification" refers to the process of assigning income and expense information to specific categories.

[0068] "Natural language processing technology" refers to the technology that enables machines to understand, analyze, and generate appropriate responses to human language.

[0069] "Notification" refers to the act of sending important information or reminders from a system to a user.

[0070] A "reminder" refers to a warning or alert message sent to a user to inform them of deadlines for income reporting or document submission.

[0071] "Format" refers to the standardized format that the generated documents must follow.

[0072] "Prompt" refers to responding or providing an answer in a short amount of time.

[0073] A description of the embodiment for carrying out the invention will be provided.

[0074] This system is designed to allow users to efficiently report their income. Users input income and expense information using their own devices and send it to the server. A dedicated application for data entry is installed on the device. This application has an input form where users can enter their salary, business income, and other related information. It is also possible to upload images of receipts and invoices using the device's camera function.

[0075] The server receives revenue information submitted by users and stores it in a database. Common software, such as MySQL®, is used for database management. The server also receives images of expense information and analyzes the information using OCR (Optical Character Recognition) technology. A suitable technology for this purpose is, for example, Google® Cloud Vision API. This allows the server to extract text information from the images, identify expense items, and calculate the total amount by utilizing a generative AI model.

[0076] Furthermore, when users input questions through their devices, the server understands them using natural language processing technology and provides answers. By utilizing generative AI models, it can generate optimal responses to questions such as, "Which expense category does this receipt belong to?" This allows users to quickly resolve their questions and proceed with the process.

[0077] Furthermore, the server automatically generates reminders and sends notifications to users' devices to inform them of approaching deadlines for income declarations and required document submissions. This ensures that important schedules are not forgotten and allows for smooth processing.

[0078] As described above, this system simplifies income reporting and provides a comprehensive support system to offer users useful information.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] Users input income and expense information using their devices. They open a dedicated application on their devices and fill in information about their salary and other income and expenses in the input form. They can also attach images of receipts and invoices using the upload function. As output from the input, income and expense information is generated in digital data format and sent to the server.

[0082] Step 2:

[0083] The server receives income information submitted by users. The server analyzes the received data and categorizes it into categories such as salary income and business income. This classification process utilizes database software (e.g., MySQL) to store the information in an appropriate format. This improves the efficiency of information processing, allowing users to automatically view the classified information.

[0084] Step 3:

[0085] The server receives an image of expense information uploaded by the user. It analyzes the image using OCR technology (e.g., Google Cloud Vision API) and extracts text information. Based on the extracted data, a generative AI model is used to identify expense items and automatically calculate the total for each item. The analysis results are stored in a database as expense information, allowing the user to check the total amount and other details.

[0086] Step 4:

[0087] Users can ask questions about their reporting process from their terminal. The server interprets the received questions using natural language processing technology. Using a generative AI model, it generates appropriate answers to the entered prompts (for example, "Which expense category does this receipt belong to?"). The answers are returned to the user in real time, ensuring quick resolution.

[0088] Step 5:

[0089] The server automatically generates reminders as income reporting deadlines and document submission deadlines approach. Using a scheduling function, it sends notifications to the user's device at the appropriate time. This ensures users don't miss important deadlines and can complete the reporting process smoothly.

[0090] (Application Example 1)

[0091] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0092] Many users face the complexities of information management in electronic transactions and require a system to simplify the cumbersome tax filing process. Furthermore, a system is needed to appropriately classify users' economic transactions and automatically store them as necessary tax information. However, current systems fail to effectively address these challenges, placing a burden on users.

[0093] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0094] In this invention, the server includes means for receiving and classifying information entered by the user, means for analyzing the entered content, identifying and calculating related items, and means for detecting economic transactions and automatically assigning them to the relevant classifications. This enables users to efficiently manage information on electronic transactions and easily obtain the data necessary for filing tax returns.

[0095] "User-entered information" refers to data that users manually or automatically provide to the system, including income and expense information.

[0096] "Classification methods" refer to the process of organizing and managing input information into categories based on specific rules or algorithms.

[0097] "Means for generating necessary documents" refers to a function that creates documents in the format required for tax and business purposes based on classified information.

[0098] "Means of analyzing content, identifying relevant items, and calculating" refers to the process of analyzing input data, identifying appropriate items, and automatically calculating their values.

[0099] "Means of providing information to users" refers to functions that enable the system to present calculation results and generated information to users in an easily understandable format.

[0100] "Methods for generating answers using natural language processing technology" refer to technologies used to analyze user questions and generate appropriate responses based on relevant information.

[0101] A "means of notifying reminders" is a system that automatically sends notifications to encourage users to take necessary actions by a specific deadline.

[0102] "A means of detecting economic transactions and automatically assigning them to relevant categories" refers to a process that captures users' economic activities in real time and sorts that information into the appropriate categories.

[0103] The system implementing this invention consists of a user terminal and a server. The user terminal accepts input of income information and expense information via an interface. To simplify user operation, it is often implemented as a smartphone or tablet application. This terminal is equipped with communication means for sending data to the server and receiving responses from the server.

[0104] The server plays a primary role in data processing. First, the server receives information sent from users and automatically classifies it using AI technology and algorithms. Specifically, it classifies income information into categories such as salary income and real estate income, and expense information into categories such as transportation expenses and communication expenses. A database engine and machine learning models are used for this.

[0105] Furthermore, the server uses natural language processing technology to generate real-time responses to user questions. This feature allows users to easily resolve any questions they have about tax matters. For example, if a user asks, "What is the limit on deductible travel expenses this year?", the server will provide an appropriate answer based on relevant laws and historical data. Generative AI models are used to improve the accuracy and speed of responses.

[0106] Furthermore, the server has the ability to automatically detect economic transactions and assign them to the appropriate categories. This is achieved through integration with electronic payment services. For example, when a user makes a payment with a credit card, the transaction information is immediately recorded as an expense. This minimizes the effort required from the user.

[0107] Examples of prompt statements are as follows:

[0108] "What are the requirements for this year's medical expense deduction?"

[0109] "To what extent are business travel expenses deductible?"

[0110] The above describes the form for carrying out the invention, and this system allows users to efficiently complete the tax return filing process.

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] Users input income and expense information using a terminal. The terminal receives this data and sends it to the server. To make the input process as easy as possible for users, an interface is provided that allows for text input and image uploads. The input data includes a wide range of information, such as numerical data and image data.

[0114] Step 2:

[0115] The server receives information sent by users and automatically classifies it based on predefined categories. This process uses a database engine to categorize income information into categories such as salary income and real estate income, and expense information into categories such as transportation and communication expenses. The classified data is recorded in a database on the server.

[0116] Step 3:

[0117] The server uses an AI model to analyze the entered expense information. Here, it extracts text from user-uploaded receipt images and invoices, identifying relevant expense items. After processing the data, it automatically calculates the total cost for each related item and stores that information in the database.

[0118] Step 4:

[0119] When a user enters a tax-related question through their device, the server uses natural language processing technology to analyze the question. Based on the analyzed question, a generative AI model queries legal data and database information to construct an appropriate answer. The generated response is immediately sent to the user's device and displayed. In this step, the input is the user's question, and the output is the relevant answer.

[0120] Step 5:

[0121] The server detects economic transactions made by users through electronic payment services and assigns them to the appropriate expense category in real time. The server receives data from electronic payment transactions and processes it automatically based on pre-configured rules and patterns. This data processing classifies expenses according to the type of transaction and stores the data in a database.

[0122] Step 6:

[0123] The server automatically generates and sends reminder notifications to the user's device as deadlines for declarations and document submissions approach. The content of the reminders is generated according to a pre-set schedule and displayed to the user as notifications. This allows users to avoid forgetting important deadlines.

[0124] 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.

[0125] This invention combines an emotion engine with a tax return support system to understand the user's emotional state and enable personalized responses accordingly. Based on data entered by the user via a terminal, this system classifies and analyzes income and expense information on a server, while simultaneously analyzing the user's emotions from their input and behavioral patterns.

[0126] The server first receives income information entered by the user on the terminal and automatically categorizes it. The categorized information is stored in a database and used for subsequent tax document generation. Furthermore, when the user enters expense information and uploads related receipts, the server uses AI technology to analyze the content. At this time, the server utilizes an emotion engine to identify the emotions the user displays while entering information and operating the system.

[0127] For example, if the server detects that a user is finding the input process cumbersome, it will suggest simpler steps or offer the option to skip steps. This is made possible by an emotion engine that detects negative emotions such as stress and anxiety in the user.

[0128] Furthermore, when a user enters a question about filing their tax return, the server uses natural language processing to analyze the question and immediately provides relevant information. It also adjusts the tone and content of the response based on emotional information. In this way, the system creates an environment where users can comfortably handle the complex tax process.

[0129] Furthermore, when the emotion engine detects positive emotions, the system simplifies its response to maintain a smooth interface. As the submission deadline approaches, it utilizes a notification function to customize emotion-based reminders and guide users at the appropriate time.

[0130] This system not only assists with tax procedures but also provides comprehensive support that takes into account the user's psychological needs. The user experience is enhanced by personalized responses, making the tax filing process smooth and comfortable.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] Users input income information through their terminals and send it to the server. During this process, users input information based on guide options, and the system verifies the input's accuracy in real time.

[0134] Step 2:

[0135] After receiving income information, the server automatically classifies it using an algorithm. The classified information is stored in a database as salary income or business income and used in subsequent processing.

[0136] Step 3:

[0137] The user enters expense information from their device and uploads images of receipts as needed. The system suggests image reading options, and proceeds to the next step once the user approves.

[0138] Step 4:

[0139] The server analyzes the uploaded receipts and extracts text using AI technology. Based on this data, it identifies expense items and automatically accounts for them as relevant expenses.

[0140] Step 5:

[0141] The emotion engine analyzes the user's input pace and actions to detect emotional signs such as stress and anxiety. For example, it measures the time when input stops to determine the possibility of negative emotions.

[0142] Step 6:

[0143] The server adapts the user interface based on the analysis results of the emotion engine. If the user is experiencing stress, the terminal will be presented with options to simplify the process.

[0144] Step 7:

[0145] The user enters their question on their device and sends it to the server. The server uses natural language processing to analyze the question and quickly provides the requested information.

[0146] Step 8:

[0147] The emotion engine re-evaluates the emotions expressed in the question and responds in an appropriate tone. If the user is feeling upset, it softens the tone of the response and uses more approachable language.

[0148] Step 9:

[0149] As the submission deadline approaches, the server sends a reminder to the user's device tailored to their emotional state. For example, a brief notification is sent if the user is emotionally calm, while a more detailed notification with an explanation is sent if anxiety is detected.

[0150] Through this process, the system not only improves the accuracy of tax processing but also provides flexible support that adapts to the user's feelings.

[0151] (Example 2)

[0152] 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".

[0153] In modern data recording tasks, many users experience significant psychological stress. In particular, inputting expense and income information presents challenges due to both data accuracy and the complexity of the process. Furthermore, these issues reduce user efficiency and increase the risk of errors. Additionally, the quality of responses to questions requires consideration of the user's psychological state, but existing technologies are insufficient in this regard.

[0154] 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.

[0155] In this invention, the server includes means for receiving and automatically classifying data entered by the user, means for detecting the user's psychological state using a behavioral analysis engine and optimizing the operation procedure accordingly, and means for notifying the user of necessary information and procedures in a timely manner. This makes it possible to reduce the user's psychological stress and realize an efficient and accurate data entry process.

[0156] A "user" refers to a person or group that uses the system to input data and make inquiries.

[0157] A "server" is a device that plays a central role in a computer system by receiving and analyzing data sent by users and performing the necessary processing.

[0158] "Income information" refers to data that represents all income a user receives, such as salary income and business income.

[0159] "Expense information" refers to data showing the costs and purchases a user has made.

[0160] "Means of automatic classification" refers to a program or algorithm that divides data received by a server into specific categories.

[0161] A "behavioral analysis engine" is a technology that analyzes a user's psychological state based on their actions and input patterns, and derives appropriate responses.

[0162] "Natural language processing technology" is artificial intelligence technology that enables computers to understand and interpret human language and generate appropriate responses.

[0163] A "notification" is a message sent to a user to provide important information or reminders and encourage appropriate action.

[0164] This invention provides a system that offers high operational efficiency while reducing the psychological burden on users in tax filing and other data processing. The system mainly consists of three elements: a server, a terminal, and a user.

[0165] The user first enters income and expense information through a terminal. This terminal is a computer device that provides an interface for data entry. The entered data is immediately sent to the server. The server receives the data sent from the user and classifies it into predetermined categories using an automatic classification algorithm. This classification allows for the rapid generation of various data records.

[0166] Furthermore, the server is equipped with a behavioral analysis engine that can analyze the user's input patterns and actions to determine their emotional state. For example, if a user is experiencing stress during input operations, the server will suggest ways to simplify the operation procedures. AI is used for this emotional analysis, enabling personalized responses that take into account the user's psychological aspects.

[0167] Furthermore, the server uses natural language processing technology to analyze user inquiries and generate accurate responses. This allows users to handle complex data processing and inquiries without feeling stressed.

[0168] Furthermore, the server has a notification function that sends reminders when the submission deadline is approaching. The content of the reminders is customized by a behavioral analysis engine, and users are notified at the optimal time and with the most appropriate content.

[0169] For example, if a user asks a question such as, "Which category does this expense fall into?", the server can use natural language processing to interpret the question and quickly provide relevant information. An example of a prompt for the generative AI model might be, "Can I claim this receipt as an expense? Can I simplify the process?" This allows users to process and manage data more smoothly and comfortably.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] The user enters income and expense information via their device. Specifically, they type the required data into the input form on the device and click the "Submit" button. This input data is then instructed to be sent to the server. The input includes information from the user's pay stubs and purchase receipts. This completes the first stage of processing, with the data being delivered to the server.

[0173] Step 2:

[0174] The server analyzes the received income information using an automated classification algorithm. Specifically, it connects to a database and classifies each data item into categories such as salary income and business income. The input data is stored in the database in a structured format. The output is a collection of classified income data, which facilitates subsequent data processing.

[0175] Step 3:

[0176] Expense information entered by the user and associated receipts are sent to the server. The server uses AI to analyze this data. Specifically, it uses character recognition technology to obtain text information from receipts and then classifies it into the appropriate expense category. Text data is generated from the image data received as input, and a list of expenses is output based on this. This ensures that each item is accurately accounted for.

[0177] Step 4:

[0178] The server uses a behavioral analysis engine to analyze user input and actions, and evaluates their emotional state. The input includes the user's operation speed and patterns. Specifically, it measures whether the user is experiencing frustration or stress from the operation. Based on these results, it provides the user with suggestions for simplifying the operation procedure, thereby reducing the burden of operation.

[0179] Step 5:

[0180] When a user enters a question into their device, the server uses natural language processing technology to analyze the question and generate an accurate answer. It analyzes the entered question, retrieves relevant information from a database, and combines it. The output is a specific answer to the question, which is then sent to the user. This resolves the user's doubts.

[0181] Step 6:

[0182] The server uses a function that automatically generates reminders and notifies the user as the submission deadline approaches. The inputs used are deadline information and the results of sentiment analysis. Specifically, reminders are created based on the user's level of anxiety or urgency. The output is a customized notification displayed on the user's device, allowing the user to take appropriate action at the right time.

[0183] (Application Example 2)

[0184] 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".

[0185] There is a need to improve the usability of tax procedures and provide an appropriate interface that responds to the user's emotional state. Traditional systems often cause users stress and anxiety, hindering the smooth progress of procedures. Furthermore, there is a lack of customizable reminder functions to ensure timely document submission and procedures.

[0186] 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.

[0187] In this invention, the server includes a module for classifying income data, a module for calculating expenditure data, and a module for suggesting actions based on the user's emotional state. This enables support for tax procedures tailored to the user's emotional state and provides a stress-reducing interface. Furthermore, by providing appropriate reminders based on emotions, it is possible to smoothly support document submission and procedures.

[0188] "Income data" refers to information that includes all financial gains earned by an individual or corporation within a specific period.

[0189] "Classification" is the process of grouping and organizing collected data according to specific criteria.

[0190] "Tax documents" are official documents required for tax-related reporting and filing.

[0191] "Expenditure data" refers to all financial information about expenditures made by an individual or corporation within a specified period.

[0192] "Calculation" is the act of performing arithmetic operations based on given numerical data to derive a result.

[0193] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0194] A "reminder" is a function that prompts you to take a specific action or notifies you so that you don't forget an important appointment.

[0195] "Emotional state" refers to an individual's feelings, mood, or psychological response at a specific time.

[0196] An "interface" is a means or device that enables interaction between a user and a computer system.

[0197] This invention is a system in which users input income and expense data using their own devices, and this data is analyzed on a server. The devices have a dedicated application installed and, based on user input, collect income data and send it to a server in the cloud. The server classifies the collected data and automatically generates the necessary tax documents. The classification of income data and the calculation of expense data are performed by a database system and modules embedded in the server. The database used is assumed to be a general relational database.

[0198] Furthermore, the server incorporates natural language processing technology to generate responses to user questions. This natural language processing utilizes Google's Natural Language Processing API to analyze user-submitted questions and responses. In addition, the server implements an emotion analysis engine to measure the user's emotional state. For example, it employs Microsoft® Azure®'s emotion analysis API to evaluate the user's stress level and anxiety in real time during input. This makes it possible to suggest operating procedures that minimize user discomfort.

[0199] For example, if the emotion engine detects that a user is frustrated while entering expense data, the server will simplify the steps and present them accordingly. Furthermore, as the submission deadline approaches, the system may send an emotion-sensitive reminder to facilitate the submission process. This reminder might include a message such as, "It's okay. You have X days left until the deadline. Is there anything we can help you with?"

[0200] An example of a prompt message might be: "Analyze the user's emotional state based on their latest input data and activity history, and generate the optimal support procedure."

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] Users input income and expense data using a terminal. The entered data is structured as formalized data through a dedicated application on the terminal and sent to a cloud server. At this stage, a basic verification is performed to check for duplicates or inconsistencies in the input data.

[0204] Step 2:

[0205] The server categorizes the received income data. It receives formalized income data entered by the user as input. The data is analyzed based on classification rules stored in the database, and the classification results are obtained. This classified data is used to generate tax documents in the next step.

[0206] Step 3:

[0207] The server analyzes spending data, identifies relevant spending items, and performs calculations. The input data is spending data sent by the user, and the data is analyzed using an AI model. As a result, calculation results such as totals and averages for each spending item are obtained and formatted for display to the user.

[0208] Step 4:

[0209] The server analyzes user-submitted questions using natural language processing (NLU) technology. The input data is the text-based questions displayed to the user. Based on the analysis, it generates answers and sends the results to the user's device. Here, the NLU library is used to extract the intent of the questions and retrieve the corresponding answers from the database.

[0210] Step 5:

[0211] The server uses an emotion analysis engine to analyze the user's emotional state in real time. Input data includes the user's operation logs and input speed during input. This data is quantified by the emotion analysis engine as the user's stress level and emotional state. Based on this analysis, the server determines how to respond to the user in the next step.

[0212] Step 6:

[0213] Based on the sentiment analysis results, the server adjusts the tone of its responses and provides optimal suggestions for the user. The input here is emotional state data obtained from the sentiment analysis engine. Based on this, simplified operation steps to explain things gently to the user and adjusted response messages to reduce stress are output.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] [Second Embodiment]

[0218] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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).

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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".

[0230] This invention provides a system that enables users to efficiently complete their tax return procedures. This system processes income and expense information entered from the user's terminal on a server, enabling the generation of necessary tax documents and real-time responses to inquiries.

[0231] The server first receives income information submitted by the user and categorizes it appropriately. For example, the server distinguishes between salary income and real estate income, and stores it in the database in a predetermined format as needed. This eliminates the need for users to manually categorize the information, significantly reducing the effort required for data entry.

[0232] Next, regarding expense information, the server receives images of receipts and invoices uploaded by the user from their device and analyzes their contents using an AI model. The server identifies expense items and automatically calculates the totals. For example, business-related transportation and communication expenses are detected and aggregated as legitimate expenses.

[0233] Users can input any questions that arise during the tax filing process into their terminals. The server uses natural language processing to analyze the user's questions and generates appropriate answers by referring to relevant tax laws and historical database information. This response is provided to the user in real time, allowing them to immediately resolve any anxieties or questions they may have during the process.

[0234] Furthermore, the server has a function that automatically generates reminders and notifies the user's device when the filing deadline or the deadline for submitting necessary documents is approaching. This allows users to complete the process smoothly without forgetting important deadlines.

[0235] As described above, this system assists users in the tax filing process by simplifying complex tax procedures and providing necessary information in a timely manner.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] Users enter income information via their device and send it to the server. Users enter their salary income and other sources of income into a dedicated form. They can select the type of income using dropdown menus or checkboxes.

[0239] Step 2:

[0240] The server processes income information received from users and classifies it into appropriate categories. Based on rules set within the server, the information is categorized into salary income, real estate income, business income, etc., and registered in the database.

[0241] Step 3:

[0242] Users enter expense information into their terminal and upload images of relevant receipts to the server. They enter the type and amount of the expense into a form and attach photos of the receipts.

[0243] Step 4:

[0244] The server analyzes the uploaded receipt image and automatically extracts expense items using AI technology. An image processing algorithm recognizes the text, automatically classifies it into categories such as transportation expenses and communication expenses, and performs calculations.

[0245] Step 5:

[0246] The server generates the necessary tax documents based on aggregated income and expense information. It creates the documents in the latest format corresponding to the tax year and generates files for user review.

[0247] Step 6:

[0248] Users can input questions about their tax return process from their terminal. If they have a question, they enter it in the text form and send it to the server.

[0249] Step 7:

[0250] The server uses natural language processing to analyze the user's question and generate an appropriate answer. It refers to relevant laws and historical data to generate the answer text and send it back to the terminal.

[0251] Step 8:

[0252] The server sets reminders for important deadlines and sends notifications to the user's device as the submission deadline approaches. Based on the reminder settings, it also sends push notifications and emails to alert users.

[0253] This series of processes allows users to efficiently handle complex tax procedures and receive necessary information and support in real time.

[0254] (Example 1)

[0255] 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."

[0256] Traditional tax procedures require users to manually input and categorize their income and expense information, which is time-consuming and laborious. Furthermore, there is no means to quickly obtain answers to questions, and there is a risk of forgetting to submit the appropriate documents on time. Additionally, if the generated document formats are incompatible, delays in the process can occur.

[0257] 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.

[0258] In this invention, the server includes means for receiving and classifying income information entered by the user, means for analyzing entered expense information, identifying and calculating related expense items, and means for receiving questions from the user and generating answers using natural language processing technology. This enables the user to efficiently manage income and expense information, quickly resolve questions, and submit accurate documents within the appropriate timeframe.

[0259] A "user" refers to a person who uses the system to input income and expense information and receives the processing results.

[0260] "Income information" refers to data related to monetary receipts, such as salaries and business income.

[0261] "Expense information" refers to data related to expenditures incurred in the course of business operations.

[0262] "Classification" refers to the process of assigning income and expense information to specific categories.

[0263] "Natural language processing technology" refers to the technology that enables machines to understand, analyze, and generate appropriate responses to human language.

[0264] "Notification" refers to the act of sending important information or reminders from a system to a user.

[0265] A "reminder" refers to a warning or alert message sent to a user to inform them of deadlines for income reporting or document submission.

[0266] "Format" refers to the standardized format that the generated documents must follow.

[0267] "Prompt" refers to responding or providing an answer in a short amount of time.

[0268] A description of the embodiment for carrying out the invention will be provided.

[0269] This system is designed to allow users to efficiently report their income. Users input income and expense information using their own devices and send it to the server. A dedicated application for data entry is installed on the device. This application has an input form where users can enter their salary, business income, and other related information. It is also possible to upload images of receipts and invoices using the device's camera function.

[0270] The server receives revenue information submitted by users and stores it in a database. Common software, such as MySQL, is used for database management. The server also receives images of expense information and analyzes the information using OCR (Optical Character Recognition) technology. A suitable technology for this purpose is, for example, the Google Cloud Vision API. This allows the server to extract text information from the image, identify expense items, and calculate the total amount by utilizing a generative AI model.

[0271] Furthermore, when users input questions through their devices, the server understands them using natural language processing technology and provides answers. By utilizing generative AI models, it can generate optimal responses to questions such as, "Which expense category does this receipt belong to?" This allows users to quickly resolve their questions and proceed with the process.

[0272] Furthermore, the server automatically generates reminders and sends notifications to users' devices to inform them of approaching deadlines for income declarations and required document submissions. This ensures that important schedules are not forgotten and allows for smooth processing.

[0273] As described above, this system simplifies income reporting and provides a comprehensive support system to offer users useful information.

[0274] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0275] Step 1:

[0276] Users input income and expense information using their devices. They open a dedicated application on their devices and fill in information about their salary and other income and expenses in the input form. They can also attach images of receipts and invoices using the upload function. As output from the input, income and expense information is generated in digital data format and sent to the server.

[0277] Step 2:

[0278] The server receives the income information sent by the user. The server analyzes the received data and classifies it into categories such as salary income and business income. In this classification operation, database software (e.g., MySQL) is used to store the information in an appropriate format. This improves the efficiency of information processing, and the user can automatically view the classified information.

[0279] Step 3:

[0280] The server receives the image of the expense information uploaded by the user. The OCR technology (e.g., Google Cloud Vision API) is used to analyze the image and extract the character information. Based on the extracted data, a generative AI model is used to identify the expense items, and the total is automatically calculated for each item. The analysis result is stored in the database as expense information, and the user can check the total amount, etc.

[0281] Step 4:

[0282] The user can ask questions about the declaration from the terminal. The server interprets the received questions using natural language processing technology. Using a generative AI model, an appropriate answer to the input prompt sentence (e.g., "Which expense category is this receipt classified into?") is created. The answer is returned to the user in real time, enabling quick resolution.

[0283] Step 5:

[0284] When the deadline for income declaration and the deadline for submitting required documents approach, the server generates an automatic reminder. Using the scheduling function, a notification is sent to the user's terminal at an appropriate time. This enables the user to avoid missing important deadlines and complete the declaration procedure smoothly.

[0285] (Application Example 1)

[0286] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0287] There is a need to eliminate the complexity of information management in electronic transactions faced by many users and simplify the cumbersome operations in the final tax return procedures. In addition, there is a need for a system that appropriately classifies the economic transactions made by users and automatically accumulates them as necessary tax information. However, the current system cannot effectively solve these problems, which has become a burden on users.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0289] In this invention, the server includes: means for receiving and classifying information input by a user; means for analyzing the input content, identifying relevant items, and performing calculations; means for detecting economic transactions and automatically assigning them to relevant classifications. As a result, the user can efficiently manage the information of electronic transactions and easily obtain the data required for the final tax return procedures.

[0290] "Information input by a user" refers to data provided by the user to the system manually or automatically, which includes income information and expense information.

[0291] "Means for classifying" is a process for sorting and managing the input information by category based on specific rules or algorithms.

[0292] "Means for generating necessary documents" is a function for creating documents in a format required for tax or business purposes based on the classified information.

[0293] "Means of analyzing content, identifying relevant items, and calculating" refers to the process of analyzing input data, identifying appropriate items, and automatically calculating their values.

[0294] "Means of providing information to users" refers to functions that enable the system to present calculation results and generated information to users in an easily understandable format.

[0295] "Methods for generating answers using natural language processing technology" refer to technologies used to analyze user questions and generate appropriate responses based on relevant information.

[0296] A "means of notifying reminders" is a system that automatically sends notifications to encourage users to take necessary actions by a specific deadline.

[0297] "A means of detecting economic transactions and automatically assigning them to relevant categories" refers to a process that captures users' economic activities in real time and sorts that information into the appropriate categories.

[0298] The system implementing this invention consists of a user terminal and a server. The user terminal accepts input of income information and expense information via an interface. To simplify user operation, it is often implemented as a smartphone or tablet application. This terminal is equipped with communication means for sending data to the server and receiving responses from the server.

[0299] The server plays a primary role in data processing. First, the server receives information sent from users and automatically classifies it using AI technology and algorithms. Specifically, it classifies income information into categories such as salary income and real estate income, and expense information into categories such as transportation expenses and communication expenses. A database engine and machine learning models are used for this.

[0300] Furthermore, the server uses natural language processing technology to generate real-time responses to questions from users. With this function, users can easily resolve their doubts regarding taxation. For example, if a user asks a question such as "What is the range of transportation expenses deductible this year?", an appropriate answer will be presented based on relevant laws and past data. The generative AI model is utilized to enhance the accuracy and speed of the responses.

[0301] In addition, the server has the function of automatically detecting economic transactions and assigning them to appropriate categories. This is achieved through cooperation with electronic payment services. For example, when a user makes a payment with a credit card, the transaction information is immediately recorded as an expense. This enables minimizing the user's effort.

[0302] Examples of prompt sentences are as follows:

[0303] "What are the conditions for medical expense deductions this year?"

[0304] "Up to what extent are business trip expenses recognized as expenses?"

[0305] The above is the form for implementing the invention, and with this system, users can efficiently carry out the final tax return procedures.

[0306] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0307] Step 1:

[0308] The user inputs income information and expense information using the terminal. The terminal receives this data and transmits it to the server. When inputting, an interface that enables text input and image upload is provided so that the user can operate as easily as possible. The data to be input covers a wide range, such as numerical information and image data.

[0309] Step 2:

[0310] The server receives information sent by users and automatically classifies it based on predefined categories. This process uses a database engine to categorize income information into categories such as salary income and real estate income, and expense information into categories such as transportation and communication expenses. The classified data is recorded in a database on the server.

[0311] Step 3:

[0312] The server uses an AI model to analyze the entered expense information. Here, it extracts text from user-uploaded receipt images and invoices, identifying relevant expense items. After processing the data, it automatically calculates the total cost for each related item and stores that information in the database.

[0313] Step 4:

[0314] When a user enters a tax-related question through their device, the server uses natural language processing technology to analyze the question. Based on the analyzed question, a generative AI model queries legal data and database information to construct an appropriate answer. The generated response is immediately sent to the user's device and displayed. In this step, the input is the user's question, and the output is the relevant answer.

[0315] Step 5:

[0316] The server detects economic transactions made by users through electronic payment services and assigns them to the appropriate expense category in real time. The server receives data from electronic payment transactions and processes it automatically based on pre-configured rules and patterns. This data processing classifies expenses according to the type of transaction and stores the data in a database.

[0317] Step 6:

[0318] The server automatically generates and sends reminder notifications to the user's device as deadlines for declarations and document submissions approach. The content of the reminders is generated according to a pre-set schedule and displayed to the user as notifications. This allows users to avoid forgetting important deadlines.

[0319] 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.

[0320] This invention combines an emotion engine with a tax return support system to understand the user's emotional state and enable personalized responses accordingly. Based on data entered by the user via a terminal, this system classifies and analyzes income and expense information on a server, while simultaneously analyzing the user's emotions from their input and behavioral patterns.

[0321] The server first receives income information entered by the user on the terminal and automatically categorizes it. The categorized information is stored in a database and used for subsequent tax document generation. Furthermore, when the user enters expense information and uploads related receipts, the server uses AI technology to analyze the content. At this time, the server utilizes an emotion engine to identify the emotions the user displays while entering information and operating the system.

[0322] For example, if the server detects that a user is finding the input process cumbersome, it will suggest simpler steps or offer the option to skip steps. This is made possible by an emotion engine that detects negative emotions such as stress and anxiety in the user.

[0323] Furthermore, when a user enters a question about filing their tax return, the server uses natural language processing to analyze the question and immediately provides relevant information. It also adjusts the tone and content of the response based on emotional information. In this way, the system creates an environment where users can comfortably handle the complex tax process.

[0324] Furthermore, when the emotion engine detects positive emotions, the system simplifies its response to maintain a smooth interface. As the submission deadline approaches, it utilizes a notification function to customize emotion-based reminders and guide users at the appropriate time.

[0325] This system not only assists with tax procedures but also provides comprehensive support that takes into account the user's psychological needs. The user experience is enhanced by personalized responses, making the tax filing process smooth and comfortable.

[0326] The following describes the processing flow.

[0327] Step 1:

[0328] Users input income information through their terminals and send it to the server. During this process, users input information based on guide options, and the system verifies the input's accuracy in real time.

[0329] Step 2:

[0330] After receiving income information, the server automatically classifies it using an algorithm. The classified information is stored in a database as salary income or business income and used in subsequent processing.

[0331] Step 3:

[0332] The user enters expense information from their device and uploads images of receipts as needed. The system suggests image reading options, and proceeds to the next step once the user approves.

[0333] Step 4:

[0334] The server analyzes the uploaded receipts and extracts text using AI technology. Based on this data, it identifies expense items and automatically accounts for them as relevant expenses.

[0335] Step 5:

[0336] The emotion engine analyzes the user's input pace and actions to detect emotional signs such as stress and anxiety. For example, it measures the time when input stops to determine the possibility of negative emotions.

[0337] Step 6:

[0338] The server adapts the user interface based on the analysis results of the emotion engine. If the user is experiencing stress, the terminal will be presented with options to simplify the process.

[0339] Step 7:

[0340] The user enters their question on their device and sends it to the server. The server uses natural language processing to analyze the question and quickly provides the requested information.

[0341] Step 8:

[0342] The emotion engine re-evaluates the emotions expressed in the question and responds in an appropriate tone. If the user is feeling upset, it softens the tone of the response and uses more approachable language.

[0343] Step 9:

[0344] As the submission deadline approaches, the server sends a reminder to the user's device tailored to their emotional state. For example, a brief notification is sent if the user is emotionally calm, while a more detailed notification with an explanation is sent if anxiety is detected.

[0345] Through this process, the system not only improves the accuracy of tax processing but also provides flexible support that adapts to the user's feelings.

[0346] (Example 2)

[0347] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0348] In modern data recording tasks, many users experience significant psychological stress. In particular, inputting expense and income information presents challenges due to both data accuracy and the complexity of the process. Furthermore, these issues reduce user efficiency and increase the risk of errors. Additionally, the quality of responses to questions requires consideration of the user's psychological state, but existing technologies are insufficient in this regard.

[0349] 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.

[0350] In this invention, the server includes means for receiving and automatically classifying data entered by the user, means for detecting the user's psychological state using a behavioral analysis engine and optimizing the operation procedure accordingly, and means for notifying the user of necessary information and procedures in a timely manner. This makes it possible to reduce the user's psychological stress and realize an efficient and accurate data entry process.

[0351] A "user" refers to a person or group that uses the system to input data and make inquiries.

[0352] A "server" is a device that plays a central role in a computer system by receiving and analyzing data sent by users and performing the necessary processing.

[0353] "Income information" refers to data that represents all income a user receives, such as salary income and business income.

[0354] "Expense information" refers to data showing the costs and purchases a user has made.

[0355] "Means of automatic classification" refers to a program or algorithm that divides data received by a server into specific categories.

[0356] A "behavioral analysis engine" is a technology that analyzes a user's psychological state based on their actions and input patterns, and derives appropriate responses.

[0357] "Natural language processing technology" is artificial intelligence technology that enables computers to understand and interpret human language and generate appropriate responses.

[0358] A "notification" is a message sent to a user to provide important information or reminders and encourage appropriate action.

[0359] This invention provides a system that offers high operational efficiency while reducing the psychological burden on users in tax filing and other data processing. The system mainly consists of three elements: a server, a terminal, and a user.

[0360] The user first enters income and expense information through a terminal. This terminal is a computer device that provides an interface for data entry. The entered data is immediately sent to the server. The server receives the data sent from the user and classifies it into predetermined categories using an automatic classification algorithm. This classification allows for the rapid generation of various data records.

[0361] Furthermore, the server is equipped with a behavioral analysis engine that can analyze the user's input patterns and actions to determine their emotional state. For example, if a user is experiencing stress during input operations, the server will suggest ways to simplify the operation procedures. AI is used for this emotional analysis, enabling personalized responses that take into account the user's psychological aspects.

[0362] Furthermore, the server uses natural language processing technology to analyze user inquiries and generate accurate responses. This allows users to handle complex data processing and inquiries without feeling stressed.

[0363] Furthermore, the server has a notification function that sends reminders when the submission deadline is approaching. The content of the reminders is customized by a behavioral analysis engine, and users are notified at the optimal time and with the most appropriate content.

[0364] For example, if a user asks a question such as, "Which category does this expense fall into?", the server can use natural language processing to interpret the question and quickly provide relevant information. An example of a prompt for the generative AI model might be, "Can I claim this receipt as an expense? Can I simplify the process?" This allows users to process and manage data more smoothly and comfortably.

[0365] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0366] Step 1:

[0367] The user enters income and expense information via their device. Specifically, they type the required data into the input form on the device and click the "Submit" button. This input data is then instructed to be sent to the server. The input includes information from the user's pay stubs and purchase receipts. This completes the first stage of processing, with the data being delivered to the server.

[0368] Step 2:

[0369] The server analyzes the received income information using an automated classification algorithm. Specifically, it connects to a database and classifies each data item into categories such as salary income and business income. The input data is stored in the database in a structured format. The output is a collection of classified income data, which facilitates subsequent data processing.

[0370] Step 3:

[0371] Expense information entered by the user and associated receipts are sent to the server. The server uses AI to analyze this data. Specifically, it uses character recognition technology to obtain text information from receipts and then classifies it into the appropriate expense category. Text data is generated from the image data received as input, and a list of expenses is output based on this. This ensures that each item is accurately accounted for.

[0372] Step 4:

[0373] The server uses a behavioral analysis engine to analyze user input and actions, and evaluates their emotional state. The input includes the user's operation speed and patterns. Specifically, it measures whether the user is experiencing frustration or stress from the operation. Based on these results, it provides the user with suggestions for simplifying the operation procedure, thereby reducing the burden of operation.

[0374] Step 5:

[0375] When a user enters a question into their device, the server uses natural language processing technology to analyze the question and generate an accurate answer. It analyzes the entered question, retrieves relevant information from a database, and combines it. The output is a specific answer to the question, which is then sent to the user. This resolves the user's doubts.

[0376] Step 6:

[0377] The server uses a function that automatically generates reminders and notifies the user as the submission deadline approaches. The inputs used are deadline information and the results of sentiment analysis. Specifically, reminders are created based on the user's level of anxiety or urgency. The output is a customized notification displayed on the user's device, allowing the user to take appropriate action at the right time.

[0378] (Application Example 2)

[0379] 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."

[0380] There is a need to improve the usability of tax procedures and provide an appropriate interface that responds to the user's emotional state. Traditional systems often cause users stress and anxiety, hindering the smooth progress of procedures. Furthermore, there is a lack of customizable reminder functions to ensure timely document submission and procedures.

[0381] 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.

[0382] In this invention, the server includes a module for classifying income data, a module for calculating expenditure data, and a module for suggesting actions based on the user's emotional state. This enables support for tax procedures tailored to the user's emotional state and provides a stress-reducing interface. Furthermore, by providing appropriate reminders based on emotions, it is possible to smoothly support document submission and procedures.

[0383] "Income data" refers to information that includes all financial gains earned by an individual or corporation within a specific period.

[0384] "Classification" is the process of grouping and organizing collected data according to specific criteria.

[0385] "Tax documents" are official documents required for tax-related reporting and filing.

[0386] "Expenditure data" refers to all financial information about expenditures made by an individual or corporation within a specified period.

[0387] "Calculation" is the act of performing arithmetic operations based on given numerical data to derive a result.

[0388] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0389] A "reminder" is a function that prompts you to take a specific action or notifies you so that you don't forget an important appointment.

[0390] "Emotional state" refers to an individual's feelings, mood, or psychological response at a specific time.

[0391] An "interface" is a means or device that enables interaction between a user and a computer system.

[0392] This invention is a system in which users input income and expense data using their own devices, and this data is analyzed on a server. The devices have a dedicated application installed and, based on user input, collect income data and send it to a server in the cloud. The server classifies the collected data and automatically generates the necessary tax documents. The classification of income data and the calculation of expense data are performed by a database system and modules embedded in the server. The database used is assumed to be a general relational database.

[0393] Furthermore, the server incorporates natural language processing technology to generate responses to user questions. This natural language processing utilizes Google's Natural Language Processing API to analyze user-submitted questions and responses. In addition, the server implements an emotion analysis engine to measure the user's emotional state. For example, it employs Microsoft Azure's emotion analysis API to assess the user's stress level and anxiety in real time during input. This makes it possible to suggest operating procedures that minimize user discomfort.

[0394] For example, if the emotion engine detects that a user is frustrated while entering expense data, the server will simplify the steps and present them accordingly. Furthermore, as the submission deadline approaches, the system may send an emotion-sensitive reminder to facilitate the submission process. This reminder might include a message such as, "It's okay. You have X days left until the deadline. Is there anything we can help you with?"

[0395] An example of a prompt message might be: "Analyze the user's emotional state based on their latest input data and activity history, and generate the optimal support procedure."

[0396] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0397] Step 1:

[0398] Users input income and expense data using a terminal. The entered data is structured as formalized data through a dedicated application on the terminal and sent to a cloud server. At this stage, a basic verification is performed to check for duplicates or inconsistencies in the input data.

[0399] Step 2:

[0400] The server categorizes the received income data. It receives formalized income data entered by the user as input. The data is analyzed based on classification rules stored in the database, and the classification results are obtained. This classified data is used to generate tax documents in the next step.

[0401] Step 3:

[0402] The server analyzes spending data, identifies relevant spending items, and performs calculations. The input data is spending data sent by the user, and the data is analyzed using an AI model. As a result, calculation results such as totals and averages for each spending item are obtained and formatted for display to the user.

[0403] Step 4:

[0404] The server analyzes user-submitted questions using natural language processing (NLU) technology. The input data is the text-based questions displayed to the user. Based on the analysis, it generates answers and sends the results to the user's device. Here, the NLU library is used to extract the intent of the questions and retrieve the corresponding answers from the database.

[0405] Step 5:

[0406] The server uses an emotion analysis engine to analyze the user's emotional state in real time. Input data includes the user's operation logs and input speed during input. This data is quantified by the emotion analysis engine as the user's stress level and emotional state. Based on this analysis, the server determines how to respond to the user in the next step.

[0407] Step 6:

[0408] Based on the sentiment analysis results, the server adjusts the tone of its responses and provides optimal suggestions for the user. The input here is emotional state data obtained from the sentiment analysis engine. Based on this, simplified operation steps to explain things gently to the user and adjusted response messages to reduce stress are output.

[0409] 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.

[0410] 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.

[0411] 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.

[0412] [Third Embodiment]

[0413] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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).

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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".

[0425] This invention provides a system that enables users to efficiently complete their tax return procedures. This system processes income and expense information entered from the user's terminal on a server, enabling the generation of necessary tax documents and real-time responses to inquiries.

[0426] The server first receives income information submitted by the user and categorizes it appropriately. For example, the server distinguishes between salary income and real estate income, and stores it in the database in a predetermined format as needed. This eliminates the need for users to manually categorize the information, significantly reducing the effort required for data entry.

[0427] Next, regarding expense information, the server receives images of receipts and invoices uploaded by the user from their device and analyzes their contents using an AI model. The server identifies expense items and automatically calculates the totals. For example, business-related transportation and communication expenses are detected and aggregated as legitimate expenses.

[0428] Users can input any questions that arise during the tax filing process into their terminals. The server uses natural language processing to analyze the user's questions and generates appropriate answers by referring to relevant tax laws and historical database information. This response is provided to the user in real time, allowing them to immediately resolve any anxieties or questions they may have during the process.

[0429] Furthermore, the server has a function that automatically generates reminders and notifies the user's device when the filing deadline or the deadline for submitting necessary documents is approaching. This allows users to complete the process smoothly without forgetting important deadlines.

[0430] As described above, this system assists users in the tax filing process by simplifying complex tax procedures and providing necessary information in a timely manner.

[0431] The following describes the processing flow.

[0432] Step 1:

[0433] Users enter income information via their device and send it to the server. Users enter their salary income and other sources of income into a dedicated form. They can select the type of income using dropdown menus or checkboxes.

[0434] Step 2:

[0435] The server processes income information received from users and classifies it into appropriate categories. Based on rules set within the server, the information is categorized into salary income, real estate income, business income, etc., and registered in the database.

[0436] Step 3:

[0437] Users enter expense information into their terminal and upload images of relevant receipts to the server. They enter the type and amount of the expense into a form and attach photos of the receipts.

[0438] Step 4:

[0439] The server analyzes the uploaded receipt image and automatically extracts expense items using AI technology. An image processing algorithm recognizes the text, automatically classifies it into categories such as transportation expenses and communication expenses, and performs calculations.

[0440] Step 5:

[0441] The server generates the necessary tax documents based on aggregated income and expense information. It creates the documents in the latest format corresponding to the tax year and generates files for user review.

[0442] Step 6:

[0443] Users can input questions about their tax return process from their terminal. If they have a question, they enter it in the text form and send it to the server.

[0444] Step 7:

[0445] The server uses natural language processing to analyze the user's question and generate an appropriate answer. It refers to relevant laws and historical data to generate the answer text and send it back to the terminal.

[0446] Step 8:

[0447] The server sets reminders for important deadlines and sends notifications to the user's device as the submission deadline approaches. Based on the reminder settings, it also sends push notifications and emails to alert users.

[0448] This series of processes allows users to efficiently handle complex tax procedures and receive necessary information and support in real time.

[0449] (Example 1)

[0450] 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."

[0451] Traditional tax procedures require users to manually input and categorize their income and expense information, which is time-consuming and laborious. Furthermore, there is no means to quickly obtain answers to questions, and there is a risk of forgetting to submit the appropriate documents on time. Additionally, if the generated document formats are incompatible, delays in the process can occur.

[0452] 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.

[0453] In this invention, the server includes means for receiving and classifying income information entered by the user, means for analyzing entered expense information, identifying and calculating related expense items, and means for receiving questions from the user and generating answers using natural language processing technology. This enables the user to efficiently manage income and expense information, quickly resolve questions, and submit accurate documents within the appropriate timeframe.

[0454] A "user" refers to a person who uses the system to input income and expense information and receives the processing results.

[0455] "Income information" refers to data related to monetary receipts, such as salaries and business income.

[0456] "Expense information" refers to data related to expenditures incurred in the course of business operations.

[0457] "Classification" refers to the process of assigning income and expense information to specific categories.

[0458] "Natural language processing technology" refers to the technology that enables machines to understand, analyze, and generate appropriate responses to human language.

[0459] "Notification" refers to the act of sending important information or reminders from a system to a user.

[0460] A "reminder" refers to a warning or alert message sent to a user to inform them of deadlines for income reporting or document submission.

[0461] "Format" refers to the standardized format that the generated documents must follow.

[0462] "Prompt" refers to responding or providing an answer in a short amount of time.

[0463] A description of the embodiment for carrying out the invention will be provided.

[0464] This system is designed to allow users to efficiently report their income. Users input income and expense information using their own devices and send it to the server. A dedicated application for data entry is installed on the device. This application has an input form where users can enter their salary, business income, and other related information. It is also possible to upload images of receipts and invoices using the device's camera function.

[0465] The server receives revenue information submitted by users and stores it in a database. Common software, such as MySQL, is used for database management. The server also receives images of expense information and analyzes the information using OCR (Optical Character Recognition) technology. A suitable technology for this purpose is, for example, the Google Cloud Vision API. This allows the server to extract text information from the image, identify expense items, and calculate the total amount by utilizing a generative AI model.

[0466] Furthermore, when users input questions through their devices, the server understands them using natural language processing technology and provides answers. By utilizing generative AI models, it can generate optimal responses to questions such as, "Which expense category does this receipt belong to?" This allows users to quickly resolve their questions and proceed with the process.

[0467] Furthermore, the server automatically generates reminders and sends notifications to users' devices to inform them of approaching deadlines for income declarations and required document submissions. This ensures that important schedules are not forgotten and allows for smooth processing.

[0468] As described above, this system simplifies income reporting and provides a comprehensive support system to offer users useful information.

[0469] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0470] Step 1:

[0471] Users input income and expense information using their devices. They open a dedicated application on their devices and fill in information about their salary and other income and expenses in the input form. They can also attach images of receipts and invoices using the upload function. As output from the input, income and expense information is generated in digital data format and sent to the server.

[0472] Step 2:

[0473] The server receives income information submitted by users. The server analyzes the received data and categorizes it into categories such as salary income and business income. This classification process utilizes database software (e.g., MySQL) to store the information in an appropriate format. This improves the efficiency of information processing, allowing users to automatically view the classified information.

[0474] Step 3:

[0475] The server receives an image of expense information uploaded by the user. It analyzes the image using OCR technology (e.g., Google Cloud Vision API) and extracts text information. Based on the extracted data, a generative AI model is used to identify expense items and automatically calculate the total for each item. The analysis results are stored in a database as expense information, allowing the user to check the total amount and other details.

[0476] Step 4:

[0477] Users can ask questions about their reporting process from their terminal. The server interprets the received questions using natural language processing technology. Using a generative AI model, it generates appropriate answers to the entered prompts (for example, "Which expense category does this receipt belong to?"). The answers are returned to the user in real time, ensuring quick resolution.

[0478] Step 5:

[0479] The server automatically generates reminders as income reporting deadlines and document submission deadlines approach. Using a scheduling function, it sends notifications to the user's device at the appropriate time. This ensures users don't miss important deadlines and can complete the reporting process smoothly.

[0480] (Application Example 1)

[0481] 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."

[0482] Many users face the complexities of information management in electronic transactions and require a system to simplify the cumbersome tax filing process. Furthermore, a system is needed to appropriately classify users' economic transactions and automatically store them as necessary tax information. However, current systems fail to effectively address these challenges, placing a burden on users.

[0483] 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.

[0484] In this invention, the server includes means for receiving and classifying information entered by the user, means for analyzing the entered content, identifying and calculating related items, and means for detecting economic transactions and automatically assigning them to the relevant classifications. This enables users to efficiently manage information on electronic transactions and easily obtain the data necessary for filing tax returns.

[0485] "User-entered information" refers to data that users manually or automatically provide to the system, including income and expense information.

[0486] "Classification methods" refer to the process of organizing and managing input information into categories based on specific rules or algorithms.

[0487] "Means for generating necessary documents" refers to a function that creates documents in the format required for tax and business purposes based on classified information.

[0488] "Means of analyzing content, identifying relevant items, and calculating" refers to the process of analyzing input data, identifying appropriate items, and automatically calculating their values.

[0489] "Means of providing information to users" refers to functions that enable the system to present calculation results and generated information to users in an easily understandable format.

[0490] "Methods for generating answers using natural language processing technology" refer to technologies used to analyze user questions and generate appropriate responses based on relevant information.

[0491] A "means of notifying reminders" is a system that automatically sends notifications to encourage users to take necessary actions by a specific deadline.

[0492] "A means of detecting economic transactions and automatically assigning them to relevant categories" refers to a process that captures users' economic activities in real time and sorts that information into the appropriate categories.

[0493] The system implementing this invention consists of a user terminal and a server. The user terminal accepts input of income information and expense information via an interface. To simplify user operation, it is often implemented as a smartphone or tablet application. This terminal is equipped with communication means for sending data to the server and receiving responses from the server.

[0494] The server plays a primary role in data processing. First, the server receives information sent from users and automatically classifies it using AI technology and algorithms. Specifically, it classifies income information into categories such as salary income and real estate income, and expense information into categories such as transportation expenses and communication expenses. A database engine and machine learning models are used for this.

[0495] Furthermore, the server uses natural language processing technology to generate real-time responses to user questions. This feature allows users to easily resolve any questions they have about tax matters. For example, if a user asks, "What is the limit on deductible travel expenses this year?", the server will provide an appropriate answer based on relevant laws and historical data. Generative AI models are used to improve the accuracy and speed of responses.

[0496] Furthermore, the server has the ability to automatically detect economic transactions and assign them to the appropriate categories. This is achieved through integration with electronic payment services. For example, when a user makes a payment with a credit card, the transaction information is immediately recorded as an expense. This minimizes the effort required from the user.

[0497] Examples of prompt statements are as follows:

[0498] "What are the requirements for this year's medical expense deduction?"

[0499] "To what extent are business travel expenses deductible?"

[0500] The above describes the form for carrying out the invention, and this system allows users to efficiently complete the tax return filing process.

[0501] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0502] Step 1:

[0503] Users input income and expense information using a terminal. The terminal receives this data and sends it to the server. To make the input process as easy as possible for users, an interface is provided that allows for text input and image uploads. The input data includes a wide range of information, such as numerical data and image data.

[0504] Step 2:

[0505] The server receives information sent by users and automatically classifies it based on predefined categories. This process uses a database engine to categorize income information into categories such as salary income and real estate income, and expense information into categories such as transportation and communication expenses. The classified data is recorded in a database on the server.

[0506] Step 3:

[0507] The server uses an AI model to analyze the entered expense information. Here, it extracts text from user-uploaded receipt images and invoices, identifying relevant expense items. After processing the data, it automatically calculates the total cost for each related item and stores that information in the database.

[0508] Step 4:

[0509] When a user enters a tax-related question through their device, the server uses natural language processing technology to analyze the question. Based on the analyzed question, a generative AI model queries legal data and database information to construct an appropriate answer. The generated response is immediately sent to the user's device and displayed. In this step, the input is the user's question, and the output is the relevant answer.

[0510] Step 5:

[0511] The server detects economic transactions made by users through electronic payment services and assigns them to the appropriate expense category in real time. The server receives data from electronic payment transactions and processes it automatically based on pre-configured rules and patterns. This data processing classifies expenses according to the type of transaction and stores the data in a database.

[0512] Step 6:

[0513] The server automatically generates and sends reminder notifications to the user's device as deadlines for declarations and document submissions approach. The content of the reminders is generated according to a pre-set schedule and displayed to the user as notifications. This allows users to avoid forgetting important deadlines.

[0514] 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.

[0515] This invention combines an emotion engine with a tax return support system to understand the user's emotional state and enable personalized responses accordingly. Based on data entered by the user via a terminal, this system classifies and analyzes income and expense information on a server, while simultaneously analyzing the user's emotions from their input and behavioral patterns.

[0516] The server first receives income information entered by the user on the terminal and automatically categorizes it. The categorized information is stored in a database and used for subsequent tax document generation. Furthermore, when the user enters expense information and uploads related receipts, the server uses AI technology to analyze the content. At this time, the server utilizes an emotion engine to identify the emotions the user displays while entering information and operating the system.

[0517] For example, if the server detects that a user is finding the input process cumbersome, it will suggest simpler steps or offer the option to skip steps. This is made possible by an emotion engine that detects negative emotions such as stress and anxiety in the user.

[0518] Furthermore, when a user enters a question about filing their tax return, the server uses natural language processing to analyze the question and immediately provides relevant information. It also adjusts the tone and content of the response based on emotional information. In this way, the system creates an environment where users can comfortably handle the complex tax process.

[0519] Furthermore, when the emotion engine detects positive emotions, the system simplifies its response to maintain a smooth interface. As the submission deadline approaches, it utilizes a notification function to customize emotion-based reminders and guide users at the appropriate time.

[0520] This system not only assists with tax procedures but also provides comprehensive support that takes into account the user's psychological needs. The user experience is enhanced by personalized responses, making the tax filing process smooth and comfortable.

[0521] The following describes the processing flow.

[0522] Step 1:

[0523] Users input income information through their terminals and send it to the server. During this process, users input information based on guide options, and the system verifies the input's accuracy in real time.

[0524] Step 2:

[0525] After receiving income information, the server automatically classifies it using an algorithm. The classified information is stored in a database as salary income or business income and used in subsequent processing.

[0526] Step 3:

[0527] The user enters expense information from their device and uploads images of receipts as needed. The system suggests image reading options, and proceeds to the next step once the user approves.

[0528] Step 4:

[0529] The server analyzes the uploaded receipts and extracts text using AI technology. Based on this data, it identifies expense items and automatically accounts for them as relevant expenses.

[0530] Step 5:

[0531] The emotion engine analyzes the user's input pace and actions to detect emotional signs such as stress and anxiety. For example, it measures the time when input stops to determine the possibility of negative emotions.

[0532] Step 6:

[0533] The server adapts the user interface based on the analysis results of the emotion engine. If the user is experiencing stress, the terminal will be presented with options to simplify the process.

[0534] Step 7:

[0535] The user enters their question on their device and sends it to the server. The server uses natural language processing to analyze the question and quickly provides the requested information.

[0536] Step 8:

[0537] The emotion engine re-evaluates the emotions expressed in the question and responds in an appropriate tone. If the user is feeling upset, it softens the tone of the response and uses more approachable language.

[0538] Step 9:

[0539] As the submission deadline approaches, the server sends a reminder to the user's device tailored to their emotional state. For example, a brief notification is sent if the user is emotionally calm, while a more detailed notification with an explanation is sent if anxiety is detected.

[0540] Through this process, the system not only improves the accuracy of tax processing but also provides flexible support that adapts to the user's feelings.

[0541] (Example 2)

[0542] 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."

[0543] In modern data recording tasks, many users experience significant psychological stress. In particular, inputting expense and income information presents challenges due to both data accuracy and the complexity of the process. Furthermore, these issues reduce user efficiency and increase the risk of errors. Additionally, the quality of responses to questions requires consideration of the user's psychological state, but existing technologies are insufficient in this regard.

[0544] 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.

[0545] In this invention, the server includes means for receiving and automatically classifying data entered by the user, means for detecting the user's psychological state using a behavioral analysis engine and optimizing the operation procedure accordingly, and means for notifying the user of necessary information and procedures in a timely manner. This makes it possible to reduce the user's psychological stress and realize an efficient and accurate data entry process.

[0546] A "user" refers to a person or group that uses the system to input data and make inquiries.

[0547] A "server" is a device that plays a central role in a computer system by receiving and analyzing data sent by users and performing the necessary processing.

[0548] "Income information" refers to data that represents all income a user receives, such as salary income and business income.

[0549] "Expense information" refers to data showing the costs and purchases a user has made.

[0550] "Means of automatic classification" refers to a program or algorithm that divides data received by a server into specific categories.

[0551] A "behavioral analysis engine" is a technology that analyzes a user's psychological state based on their actions and input patterns, and derives appropriate responses.

[0552] "Natural language processing technology" is artificial intelligence technology that enables computers to understand and interpret human language and generate appropriate responses.

[0553] A "notification" is a message sent to a user to provide important information or reminders and encourage appropriate action.

[0554] This invention provides a system that offers high operational efficiency while reducing the psychological burden on users in tax filing and other data processing. The system mainly consists of three elements: a server, a terminal, and a user.

[0555] The user first enters income and expense information through a terminal. This terminal is a computer device that provides an interface for data entry. The entered data is immediately sent to the server. The server receives the data sent from the user and classifies it into predetermined categories using an automatic classification algorithm. This classification allows for the rapid generation of various data records.

[0556] Furthermore, the server is equipped with a behavioral analysis engine that can analyze the user's input patterns and actions to determine their emotional state. For example, if a user is experiencing stress during input operations, the server will suggest ways to simplify the operation procedures. AI is used for this emotional analysis, enabling personalized responses that take into account the user's psychological aspects.

[0557] Furthermore, the server uses natural language processing technology to analyze user inquiries and generate accurate responses. This allows users to handle complex data processing and inquiries without feeling stressed.

[0558] Furthermore, the server has a notification function that sends reminders when the submission deadline is approaching. The content of the reminders is customized by a behavioral analysis engine, and users are notified at the optimal time and with the most appropriate content.

[0559] For example, if a user asks a question such as, "Which category does this expense fall into?", the server can use natural language processing to interpret the question and quickly provide relevant information. An example of a prompt for the generative AI model might be, "Can I claim this receipt as an expense? Can I simplify the process?" This allows users to process and manage data more smoothly and comfortably.

[0560] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0561] Step 1:

[0562] The user enters income and expense information via their device. Specifically, they type the required data into the input form on the device and click the "Submit" button. This input data is then instructed to be sent to the server. The input includes information from the user's pay stubs and purchase receipts. This completes the first stage of processing, with the data being delivered to the server.

[0563] Step 2:

[0564] The server analyzes the received income information using an automated classification algorithm. Specifically, it connects to a database and classifies each data item into categories such as salary income and business income. The input data is stored in the database in a structured format. The output is a collection of classified income data, which facilitates subsequent data processing.

[0565] Step 3:

[0566] Expense information entered by the user and associated receipts are sent to the server. The server uses AI to analyze this data. Specifically, it uses character recognition technology to obtain text information from receipts and then classifies it into the appropriate expense category. Text data is generated from the image data received as input, and a list of expenses is output based on this. This ensures that each item is accurately accounted for.

[0567] Step 4:

[0568] The server uses a behavioral analysis engine to analyze user input and actions, and evaluates their emotional state. The input includes the user's operation speed and patterns. Specifically, it measures whether the user is experiencing frustration or stress from the operation. Based on these results, it provides the user with suggestions for simplifying the operation procedure, thereby reducing the burden of operation.

[0569] Step 5:

[0570] When a user enters a question into their device, the server uses natural language processing technology to analyze the question and generate an accurate answer. It analyzes the entered question, retrieves relevant information from a database, and combines it. The output is a specific answer to the question, which is then sent to the user. This resolves the user's doubts.

[0571] Step 6:

[0572] The server uses a function that automatically generates reminders and notifies the user as the submission deadline approaches. The inputs used are deadline information and the results of sentiment analysis. Specifically, reminders are created based on the user's level of anxiety or urgency. The output is a customized notification displayed on the user's device, allowing the user to take appropriate action at the right time.

[0573] (Application Example 2)

[0574] 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."

[0575] There is a need to improve the usability of tax procedures and provide an appropriate interface that responds to the user's emotional state. Traditional systems often cause users stress and anxiety, hindering the smooth progress of procedures. Furthermore, there is a lack of customizable reminder functions to ensure timely document submission and procedures.

[0576] 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.

[0577] In this invention, the server includes a module for classifying income data, a module for calculating expenditure data, and a module for suggesting actions based on the user's emotional state. This enables support for tax procedures tailored to the user's emotional state and provides a stress-reducing interface. Furthermore, by providing appropriate reminders based on emotions, it is possible to smoothly support document submission and procedures.

[0578] "Income data" refers to information that includes all financial gains earned by an individual or corporation within a specific period.

[0579] "Classification" is the process of grouping and organizing collected data according to specific criteria.

[0580] "Tax documents" are official documents required for tax-related reporting and filing.

[0581] "Expenditure data" refers to all financial information about expenditures made by an individual or corporation within a specified period.

[0582] "Calculation" is the act of performing arithmetic operations based on given numerical data to derive a result.

[0583] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0584] A "reminder" is a function that prompts you to take a specific action or notifies you so that you don't forget an important appointment.

[0585] "Emotional state" refers to an individual's feelings, mood, or psychological response at a specific time.

[0586] An "interface" is a means or device that enables interaction between a user and a computer system.

[0587] This invention is a system in which users input income and expense data using their own devices, and this data is analyzed on a server. The devices have a dedicated application installed and, based on user input, collect income data and send it to a server in the cloud. The server classifies the collected data and automatically generates the necessary tax documents. The classification of income data and the calculation of expense data are performed by a database system and modules embedded in the server. The database used is assumed to be a general relational database.

[0588] Furthermore, the server incorporates natural language processing technology to generate responses to user questions. This natural language processing utilizes Google's Natural Language Processing API to analyze user-submitted questions and responses. In addition, the server implements an emotion analysis engine to measure the user's emotional state. For example, it employs Microsoft Azure's emotion analysis API to assess the user's stress level and anxiety in real time during input. This makes it possible to suggest operating procedures that minimize user discomfort.

[0589] For example, if the emotion engine detects that a user is frustrated while entering expense data, the server will simplify the steps and present them accordingly. Furthermore, as the submission deadline approaches, the system may send an emotion-sensitive reminder to facilitate the submission process. This reminder might include a message such as, "It's okay. You have X days left until the deadline. Is there anything we can help you with?"

[0590] An example of a prompt message might be: "Analyze the user's emotional state based on their latest input data and activity history, and generate the optimal support procedure."

[0591] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0592] Step 1:

[0593] Users input income and expense data using a terminal. The entered data is structured as formalized data through a dedicated application on the terminal and sent to a cloud server. At this stage, a basic verification is performed to check for duplicates or inconsistencies in the input data.

[0594] Step 2:

[0595] The server categorizes the received income data. It receives formalized income data entered by the user as input. The data is analyzed based on classification rules stored in the database, and the classification results are obtained. This classified data is used to generate tax documents in the next step.

[0596] Step 3:

[0597] The server analyzes spending data, identifies relevant spending items, and performs calculations. The input data is spending data sent by the user, and the data is analyzed using an AI model. As a result, calculation results such as totals and averages for each spending item are obtained and formatted for display to the user.

[0598] Step 4:

[0599] The server analyzes user-submitted questions using natural language processing (NLU) technology. The input data is the text-based questions displayed to the user. Based on the analysis, it generates answers and sends the results to the user's device. Here, the NLU library is used to extract the intent of the questions and retrieve the corresponding answers from the database.

[0600] Step 5:

[0601] The server uses an emotion analysis engine to analyze the user's emotional state in real time. Input data includes the user's operation logs and input speed during input. This data is quantified by the emotion analysis engine as the user's stress level and emotional state. Based on this analysis, the server determines how to respond to the user in the next step.

[0602] Step 6:

[0603] Based on the sentiment analysis results, the server adjusts the tone of its responses and provides optimal suggestions for the user. The input here is emotional state data obtained from the sentiment analysis engine. Based on this, simplified operation steps to explain things gently to the user and adjusted response messages to reduce stress are output.

[0604] 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.

[0605] 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.

[0606] 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.

[0607] [Fourth Embodiment]

[0608] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0609] 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.

[0610] 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).

[0611] 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.

[0612] 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.

[0613] 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).

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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".

[0621] This invention provides a system that enables users to efficiently complete their tax return procedures. This system processes income and expense information entered from the user's terminal on a server, enabling the generation of necessary tax documents and real-time responses to inquiries.

[0622] The server first receives income information submitted by the user and categorizes it appropriately. For example, the server distinguishes between salary income and real estate income, and stores it in the database in a predetermined format as needed. This eliminates the need for users to manually categorize the information, significantly reducing the effort required for data entry.

[0623] Next, regarding expense information, the server receives images of receipts and invoices uploaded by the user from their device and analyzes their contents using an AI model. The server identifies expense items and automatically calculates the totals. For example, business-related transportation and communication expenses are detected and aggregated as legitimate expenses.

[0624] Users can input any questions that arise during the tax filing process into their terminals. The server uses natural language processing to analyze the user's questions and generates appropriate answers by referring to relevant tax laws and historical database information. This response is provided to the user in real time, allowing them to immediately resolve any anxieties or questions they may have during the process.

[0625] Furthermore, the server has a function that automatically generates reminders and notifies the user's device when the filing deadline or the deadline for submitting necessary documents is approaching. This allows users to complete the process smoothly without forgetting important deadlines.

[0626] As described above, this system assists users in the tax filing process by simplifying complex tax procedures and providing necessary information in a timely manner.

[0627] The following describes the processing flow.

[0628] Step 1:

[0629] Users enter income information via their device and send it to the server. Users enter their salary income and other sources of income into a dedicated form. They can select the type of income using dropdown menus or checkboxes.

[0630] Step 2:

[0631] The server processes income information received from users and classifies it into appropriate categories. Based on rules set within the server, the information is categorized into salary income, real estate income, business income, etc., and registered in the database.

[0632] Step 3:

[0633] Users enter expense information into their terminal and upload images of relevant receipts to the server. They enter the type and amount of the expense into a form and attach photos of the receipts.

[0634] Step 4:

[0635] The server analyzes the uploaded receipt image and automatically extracts expense items using AI technology. An image processing algorithm recognizes the text, automatically classifies it into categories such as transportation expenses and communication expenses, and performs calculations.

[0636] Step 5:

[0637] The server generates the necessary tax documents based on aggregated income and expense information. It creates the documents in the latest format corresponding to the tax year and generates files for user review.

[0638] Step 6:

[0639] Users can input questions about their tax return process from their terminal. If they have a question, they enter it in the text form and send it to the server.

[0640] Step 7:

[0641] The server uses natural language processing to analyze the user's question and generate an appropriate answer. It refers to relevant laws and historical data to generate the answer text and send it back to the terminal.

[0642] Step 8:

[0643] The server sets reminders for important deadlines and sends notifications to the user's device as the submission deadline approaches. Based on the reminder settings, it also sends push notifications and emails to alert users.

[0644] This series of processes allows users to efficiently handle complex tax procedures and receive necessary information and support in real time.

[0645] (Example 1)

[0646] 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".

[0647] Traditional tax procedures require users to manually input and categorize their income and expense information, which is time-consuming and laborious. Furthermore, there is no means to quickly obtain answers to questions, and there is a risk of forgetting to submit the appropriate documents on time. Additionally, if the generated document formats are incompatible, delays in the process can occur.

[0648] 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.

[0649] In this invention, the server includes means for receiving and classifying income information entered by the user, means for analyzing entered expense information, identifying and calculating related expense items, and means for receiving questions from the user and generating answers using natural language processing technology. This enables the user to efficiently manage income and expense information, quickly resolve questions, and submit accurate documents within the appropriate timeframe.

[0650] A "user" refers to a person who uses the system to input income and expense information and receives the processing results.

[0651] "Income information" refers to data related to monetary receipts, such as salaries and business income.

[0652] "Expense information" refers to data related to expenditures incurred in the course of business operations.

[0653] "Classification" refers to the process of assigning income and expense information to specific categories.

[0654] "Natural language processing technology" refers to the technology that enables machines to understand, analyze, and generate appropriate responses to human language.

[0655] "Notification" refers to the act of sending important information or reminders from a system to a user.

[0656] A "reminder" refers to a warning or alert message sent to a user to inform them of deadlines for income reporting or document submission.

[0657] "Format" refers to the standardized format that the generated documents must follow.

[0658] "Prompt" refers to responding or providing an answer in a short amount of time.

[0659] A description of the embodiment for carrying out the invention will be provided.

[0660] This system is designed to allow users to efficiently report their income. Users input income and expense information using their own devices and send it to the server. A dedicated application for data entry is installed on the device. This application has an input form where users can enter their salary, business income, and other related information. It is also possible to upload images of receipts and invoices using the device's camera function.

[0661] The server receives revenue information submitted by users and stores it in a database. Common software, such as MySQL, is used for database management. The server also receives images of expense information and analyzes the information using OCR (Optical Character Recognition) technology. A suitable technology for this purpose is, for example, the Google Cloud Vision API. This allows the server to extract text information from the image, identify expense items, and calculate the total amount by utilizing a generative AI model.

[0662] Furthermore, when users input questions through their devices, the server understands them using natural language processing technology and provides answers. By utilizing generative AI models, it can generate optimal responses to questions such as, "Which expense category does this receipt belong to?" This allows users to quickly resolve their questions and proceed with the process.

[0663] Furthermore, the server automatically generates reminders and sends notifications to users' devices to inform them of approaching deadlines for income declarations and required document submissions. This ensures that important schedules are not forgotten and allows for smooth processing.

[0664] As described above, this system simplifies income reporting and provides a comprehensive support system to offer users useful information.

[0665] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0666] Step 1:

[0667] Users input income and expense information using their devices. They open a dedicated application on their devices and fill in information about their salary and other income and expenses in the input form. They can also attach images of receipts and invoices using the upload function. As output from the input, income and expense information is generated in digital data format and sent to the server.

[0668] Step 2:

[0669] The server receives income information submitted by users. The server analyzes the received data and categorizes it into categories such as salary income and business income. This classification process utilizes database software (e.g., MySQL) to store the information in an appropriate format. This improves the efficiency of information processing, allowing users to automatically view the classified information.

[0670] Step 3:

[0671] The server receives an image of expense information uploaded by the user. It analyzes the image using OCR technology (e.g., Google Cloud Vision API) and extracts text information. Based on the extracted data, a generative AI model is used to identify expense items and automatically calculate the total for each item. The analysis results are stored in a database as expense information, allowing the user to check the total amount and other details.

[0672] Step 4:

[0673] Users can ask questions about their reporting process from their terminal. The server interprets the received questions using natural language processing technology. Using a generative AI model, it generates appropriate answers to the entered prompts (for example, "Which expense category does this receipt belong to?"). The answers are returned to the user in real time, ensuring quick resolution.

[0674] Step 5:

[0675] The server automatically generates reminders as income reporting deadlines and document submission deadlines approach. Using a scheduling function, it sends notifications to the user's device at the appropriate time. This ensures users don't miss important deadlines and can complete the reporting process smoothly.

[0676] (Application Example 1)

[0677] 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".

[0678] Many users face the complexities of information management in electronic transactions and require a system to simplify the cumbersome tax filing process. Furthermore, a system is needed to appropriately classify users' economic transactions and automatically store them as necessary tax information. However, current systems fail to effectively address these challenges, placing a burden on users.

[0679] 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.

[0680] In this invention, the server includes means for receiving and classifying information entered by the user, means for analyzing the entered content, identifying and calculating related items, and means for detecting economic transactions and automatically assigning them to the relevant classifications. This enables users to efficiently manage information on electronic transactions and easily obtain the data necessary for filing tax returns.

[0681] "User-entered information" refers to data that users manually or automatically provide to the system, including income and expense information.

[0682] "Classification methods" refer to the process of organizing and managing input information into categories based on specific rules or algorithms.

[0683] "Means for generating necessary documents" refers to a function that creates documents in the format required for tax and business purposes based on classified information.

[0684] "Means of analyzing content, identifying relevant items, and calculating" refers to the process of analyzing input data, identifying appropriate items, and automatically calculating their values.

[0685] "Means of providing information to users" refers to functions that enable the system to present calculation results and generated information to users in an easily understandable format.

[0686] "Methods for generating answers using natural language processing technology" refer to technologies used to analyze user questions and generate appropriate responses based on relevant information.

[0687] A "means of notifying reminders" is a system that automatically sends notifications to encourage users to take necessary actions by a specific deadline.

[0688] "A means of detecting economic transactions and automatically assigning them to relevant categories" refers to a process that captures users' economic activities in real time and sorts that information into the appropriate categories.

[0689] The system implementing this invention consists of a user terminal and a server. The user terminal accepts input of income information and expense information via an interface. To simplify user operation, it is often implemented as a smartphone or tablet application. This terminal is equipped with communication means for sending data to the server and receiving responses from the server.

[0690] The server plays a primary role in data processing. First, the server receives information sent from users and automatically classifies it using AI technology and algorithms. Specifically, it classifies income information into categories such as salary income and real estate income, and expense information into categories such as transportation expenses and communication expenses. A database engine and machine learning models are used for this.

[0691] Furthermore, the server uses natural language processing technology to generate real-time responses to user questions. This feature allows users to easily resolve any questions they have about tax matters. For example, if a user asks, "What is the limit on deductible travel expenses this year?", the server will provide an appropriate answer based on relevant laws and historical data. Generative AI models are used to improve the accuracy and speed of responses.

[0692] Furthermore, the server has the ability to automatically detect economic transactions and assign them to the appropriate categories. This is achieved through integration with electronic payment services. For example, when a user makes a payment with a credit card, the transaction information is immediately recorded as an expense. This minimizes the effort required from the user.

[0693] Examples of prompt statements are as follows:

[0694] "What are the requirements for this year's medical expense deduction?"

[0695] "To what extent are business travel expenses deductible?"

[0696] The above describes the form for carrying out the invention, and this system allows users to efficiently complete the tax return filing process.

[0697] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0698] Step 1:

[0699] Users input income and expense information using a terminal. The terminal receives this data and sends it to the server. To make the input process as easy as possible for users, an interface is provided that allows for text input and image uploads. The input data includes a wide range of information, such as numerical data and image data.

[0700] Step 2:

[0701] The server receives information sent by users and automatically classifies it based on predefined categories. This process uses a database engine to categorize income information into categories such as salary income and real estate income, and expense information into categories such as transportation and communication expenses. The classified data is recorded in a database on the server.

[0702] Step 3:

[0703] The server uses an AI model to analyze the entered expense information. Here, it extracts text from user-uploaded receipt images and invoices, identifying relevant expense items. After processing the data, it automatically calculates the total cost for each related item and stores that information in the database.

[0704] Step 4:

[0705] When a user enters a tax-related question through their device, the server uses natural language processing technology to analyze the question. Based on the analyzed question, a generative AI model queries legal data and database information to construct an appropriate answer. The generated response is immediately sent to the user's device and displayed. In this step, the input is the user's question, and the output is the relevant answer.

[0706] Step 5:

[0707] The server detects economic transactions made by users through electronic payment services and assigns them to the appropriate expense category in real time. The server receives data from electronic payment transactions and processes it automatically based on pre-configured rules and patterns. This data processing classifies expenses according to the type of transaction and stores the data in a database.

[0708] Step 6:

[0709] The server automatically generates and sends reminder notifications to the user's device as deadlines for declarations and document submissions approach. The content of the reminders is generated according to a pre-set schedule and displayed to the user as notifications. This allows users to avoid forgetting important deadlines.

[0710] 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.

[0711] This invention combines an emotion engine with a tax return support system to understand the user's emotional state and enable personalized responses accordingly. Based on data entered by the user via a terminal, this system classifies and analyzes income and expense information on a server, while simultaneously analyzing the user's emotions from their input and behavioral patterns.

[0712] The server first receives income information entered by the user on the terminal and automatically categorizes it. The categorized information is stored in a database and used for subsequent tax document generation. Furthermore, when the user enters expense information and uploads related receipts, the server uses AI technology to analyze the content. At this time, the server utilizes an emotion engine to identify the emotions the user displays while entering information and operating the system.

[0713] For example, if the server detects that a user is finding the input process cumbersome, it will suggest simpler steps or offer the option to skip steps. This is made possible by an emotion engine that detects negative emotions such as stress and anxiety in the user.

[0714] Furthermore, when a user enters a question about filing their tax return, the server uses natural language processing to analyze the question and immediately provides relevant information. It also adjusts the tone and content of the response based on emotional information. In this way, the system creates an environment where users can comfortably handle the complex tax process.

[0715] Furthermore, when the emotion engine detects positive emotions, the system simplifies its response to maintain a smooth interface. As the submission deadline approaches, it utilizes a notification function to customize emotion-based reminders and guide users at the appropriate time.

[0716] This system not only assists with tax procedures but also provides comprehensive support that takes into account the user's psychological needs. The user experience is enhanced by personalized responses, making the tax filing process smooth and comfortable.

[0717] The following describes the processing flow.

[0718] Step 1:

[0719] Users input income information through their terminals and send it to the server. During this process, users input information based on guide options, and the system verifies the input's accuracy in real time.

[0720] Step 2:

[0721] After receiving income information, the server automatically classifies it using an algorithm. The classified information is stored in a database as salary income or business income and used in subsequent processing.

[0722] Step 3:

[0723] The user enters expense information from their device and uploads images of receipts as needed. The system suggests image reading options, and proceeds to the next step once the user approves.

[0724] Step 4:

[0725] The server analyzes the uploaded receipts and extracts text using AI technology. Based on this data, it identifies expense items and automatically accounts for them as relevant expenses.

[0726] Step 5:

[0727] The emotion engine analyzes the user's input pace and actions to detect emotional signs such as stress and anxiety. For example, it measures the time when input stops to determine the possibility of negative emotions.

[0728] Step 6:

[0729] The server adapts the user interface based on the analysis results of the emotion engine. If the user is experiencing stress, the terminal will be presented with options to simplify the process.

[0730] Step 7:

[0731] The user enters their question on their device and sends it to the server. The server uses natural language processing to analyze the question and quickly provides the requested information.

[0732] Step 8:

[0733] The emotion engine re-evaluates the emotions expressed in the question and responds in an appropriate tone. If the user is feeling upset, it softens the tone of the response and uses more approachable language.

[0734] Step 9:

[0735] As the submission deadline approaches, the server sends a reminder to the user's device tailored to their emotional state. For example, a brief notification is sent if the user is emotionally calm, while a more detailed notification with an explanation is sent if anxiety is detected.

[0736] Through this process, the system not only improves the accuracy of tax processing but also provides flexible support that adapts to the user's feelings.

[0737] (Example 2)

[0738] 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".

[0739] In modern data recording tasks, many users experience significant psychological stress. In particular, inputting expense and income information presents challenges due to both data accuracy and the complexity of the process. Furthermore, these issues reduce user efficiency and increase the risk of errors. Additionally, the quality of responses to questions requires consideration of the user's psychological state, but existing technologies are insufficient in this regard.

[0740] 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.

[0741] In this invention, the server includes means for receiving and automatically classifying data entered by the user, means for detecting the user's psychological state using a behavioral analysis engine and optimizing the operation procedure accordingly, and means for notifying the user of necessary information and procedures in a timely manner. This makes it possible to reduce the user's psychological stress and realize an efficient and accurate data entry process.

[0742] A "user" refers to a person or group that uses the system to input data and make inquiries.

[0743] A "server" is a device that plays a central role in a computer system by receiving and analyzing data sent by users and performing the necessary processing.

[0744] "Income information" refers to data that represents all income a user receives, such as salary income and business income.

[0745] "Expense information" refers to data showing the costs and purchases a user has made.

[0746] "Means of automatic classification" refers to a program or algorithm that divides data received by a server into specific categories.

[0747] A "behavioral analysis engine" is a technology that analyzes a user's psychological state based on their actions and input patterns, and derives appropriate responses.

[0748] "Natural language processing technology" is artificial intelligence technology that enables computers to understand and interpret human language and generate appropriate responses.

[0749] A "notification" is a message sent to a user to provide important information or reminders and encourage appropriate action.

[0750] This invention provides a system that offers high operational efficiency while reducing the psychological burden on users in tax filing and other data processing. The system mainly consists of three elements: a server, a terminal, and a user.

[0751] The user first enters income and expense information through a terminal. This terminal is a computer device that provides an interface for data entry. The entered data is immediately sent to the server. The server receives the data sent from the user and classifies it into predetermined categories using an automatic classification algorithm. This classification allows for the rapid generation of various data records.

[0752] Furthermore, the server is equipped with a behavioral analysis engine that can analyze the user's input patterns and actions to determine their emotional state. For example, if a user is experiencing stress during input operations, the server will suggest ways to simplify the operation procedures. AI is used for this emotional analysis, enabling personalized responses that take into account the user's psychological aspects.

[0753] Furthermore, the server uses natural language processing technology to analyze user inquiries and generate accurate responses. This allows users to handle complex data processing and inquiries without feeling stressed.

[0754] Furthermore, the server has a notification function that sends reminders when the submission deadline is approaching. The content of the reminders is customized by a behavioral analysis engine, and users are notified at the optimal time and with the most appropriate content.

[0755] For example, if a user asks a question such as, "Which category does this expense fall into?", the server can use natural language processing to interpret the question and quickly provide relevant information. An example of a prompt for the generative AI model might be, "Can I claim this receipt as an expense? Can I simplify the process?" This allows users to process and manage data more smoothly and comfortably.

[0756] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0757] Step 1:

[0758] The user enters income and expense information via their device. Specifically, they type the required data into the input form on the device and click the "Submit" button. This input data is then instructed to be sent to the server. The input includes information from the user's pay stubs and purchase receipts. This completes the first stage of processing, with the data being delivered to the server.

[0759] Step 2:

[0760] The server analyzes the received income information using an automated classification algorithm. Specifically, it connects to a database and classifies each data item into categories such as salary income and business income. The input data is stored in the database in a structured format. The output is a collection of classified income data, which facilitates subsequent data processing.

[0761] Step 3:

[0762] Expense information entered by the user and associated receipts are sent to the server. The server uses AI to analyze this data. Specifically, it uses character recognition technology to obtain text information from receipts and then classifies it into the appropriate expense category. Text data is generated from the image data received as input, and a list of expenses is output based on this. This ensures that each item is accurately accounted for.

[0763] Step 4:

[0764] The server uses a behavioral analysis engine to analyze user input and actions, and evaluates their emotional state. The input includes the user's operation speed and patterns. Specifically, it measures whether the user is experiencing frustration or stress from the operation. Based on these results, it provides the user with suggestions for simplifying the operation procedure, thereby reducing the burden of operation.

[0765] Step 5:

[0766] When a user enters a question into their device, the server uses natural language processing technology to analyze the question and generate an accurate answer. It analyzes the entered question, retrieves relevant information from a database, and combines it. The output is a specific answer to the question, which is then sent to the user. This resolves the user's doubts.

[0767] Step 6:

[0768] The server uses a function that automatically generates reminders and notifies the user as the submission deadline approaches. The inputs used are deadline information and the results of sentiment analysis. Specifically, reminders are created based on the user's level of anxiety or urgency. The output is a customized notification displayed on the user's device, allowing the user to take appropriate action at the right time.

[0769] (Application Example 2)

[0770] 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".

[0771] There is a need to improve the usability of tax procedures and provide an appropriate interface that responds to the user's emotional state. Traditional systems often cause users stress and anxiety, hindering the smooth progress of procedures. Furthermore, there is a lack of customizable reminder functions to ensure timely document submission and procedures.

[0772] 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.

[0773] In this invention, the server includes a module for classifying income data, a module for calculating expenditure data, and a module for suggesting actions based on the user's emotional state. This enables support for tax procedures tailored to the user's emotional state and provides a stress-reducing interface. Furthermore, by providing appropriate reminders based on emotions, it is possible to smoothly support document submission and procedures.

[0774] "Income data" refers to information that includes all financial gains earned by an individual or corporation within a specific period.

[0775] "Classification" is the process of grouping and organizing collected data according to specific criteria.

[0776] "Tax documents" are official documents required for tax-related reporting and filing.

[0777] "Expenditure data" refers to all financial information about expenditures made by an individual or corporation within a specified period.

[0778] "Calculation" is the act of performing arithmetic operations based on given numerical data to derive a result.

[0779] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0780] A "reminder" is a function that prompts you to take a specific action or notifies you so that you don't forget an important appointment.

[0781] "Emotional state" refers to an individual's feelings, mood, or psychological response at a specific time.

[0782] An "interface" is a means or device that enables interaction between a user and a computer system.

[0783] This invention is a system in which users input income and expense data using their own devices, and this data is analyzed on a server. The devices have a dedicated application installed and, based on user input, collect income data and send it to a server in the cloud. The server classifies the collected data and automatically generates the necessary tax documents. The classification of income data and the calculation of expense data are performed by a database system and modules embedded in the server. The database used is assumed to be a general relational database.

[0784] Furthermore, the server incorporates natural language processing technology to generate responses to user questions. This natural language processing utilizes Google's Natural Language Processing API to analyze user-submitted questions and responses. In addition, the server implements an emotion analysis engine to measure the user's emotional state. For example, it employs Microsoft Azure's emotion analysis API to assess the user's stress level and anxiety in real time during input. This makes it possible to suggest operating procedures that minimize user discomfort.

[0785] For example, if the emotion engine detects that a user is frustrated while entering expense data, the server will simplify the steps and present them accordingly. Furthermore, as the submission deadline approaches, the system may send an emotion-sensitive reminder to facilitate the submission process. This reminder might include a message such as, "It's okay. You have X days left until the deadline. Is there anything we can help you with?"

[0786] An example of a prompt message might be: "Analyze the user's emotional state based on their latest input data and activity history, and generate the optimal support procedure."

[0787] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0788] Step 1:

[0789] Users input income and expense data using a terminal. The entered data is structured as formalized data through a dedicated application on the terminal and sent to a cloud server. At this stage, a basic verification is performed to check for duplicates or inconsistencies in the input data.

[0790] Step 2:

[0791] The server categorizes the received income data. It receives formalized income data entered by the user as input. The data is analyzed based on classification rules stored in the database, and the classification results are obtained. This classified data is used to generate tax documents in the next step.

[0792] Step 3:

[0793] The server analyzes spending data, identifies relevant spending items, and performs calculations. The input data is spending data sent by the user, and the data is analyzed using an AI model. As a result, calculation results such as totals and averages for each spending item are obtained and formatted for display to the user.

[0794] Step 4:

[0795] The server analyzes user-submitted questions using natural language processing (NLU) technology. The input data is the text-based questions displayed to the user. Based on the analysis, it generates answers and sends the results to the user's device. Here, the NLU library is used to extract the intent of the questions and retrieve the corresponding answers from the database.

[0796] Step 5:

[0797] The server uses an emotion analysis engine to analyze the user's emotional state in real time. Input data includes the user's operation logs and input speed during input. This data is quantified by the emotion analysis engine as the user's stress level and emotional state. Based on this analysis, the server determines how to respond to the user in the next step.

[0798] Step 6:

[0799] Based on the sentiment analysis results, the server adjusts the tone of its responses and provides optimal suggestions for the user. The input here is emotional state data obtained from the sentiment analysis engine. Based on this, simplified operation steps to explain things gently to the user and adjusted response messages to reduce stress are output.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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."

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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 as being incorporated by reference.

[0821] The following is further disclosed regarding the embodiments described above.

[0822] (Claim 1)

[0823] [Means for receiving and classifying income information entered by the user,

[0824] [Means for generating necessary tax documents based on classified income information,

[0825] [Means for analyzing input expense information, identifying and calculating related expense items,

[0826] [Means for providing tax information and calculation results to users,

[0827] [Means for receiving user questions and generating answers using natural language processing technology,

[0828] [Means for notifying users of necessary documents and procedures,

[0829] A system that includes this.

[0830] (Claim 2)

[0831] [Means for confirming that the generated tax documents conform to a predetermined format in the generation of tax documents, according to claim 1.

[0832] (Claim 3)

[0833] [A system according to claim 1, which provides generated tax information and answers to the user in real time.

[0834] "Example 1"

[0835] (Claim 1)

[0836] [Means for receiving and classifying income information entered by users,

[0837] [Means for generating necessary documents based on classified income information,

[0838] [Means for analyzing input expense information, identifying and calculating related expense items,

[0839] [Means for providing information and calculation results to users,

[0840] [Means for receiving questions from users and generating answers using natural language processing technology,

[0841] [Means of notifying users of necessary documents and procedures,

[0842] [Means for automatically generating reminders for users as the deadline approaches,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] [Means for confirming that the generated document conforms to a predetermined format during document generation, according to claim 1.

[0846] (Claim 3)

[0847] [A system according to claim 1, which provides generated information and answers to users quickly.

[0848] "Application Example 1"

[0849] (Claim 1)

[0850] [Means for receiving and classifying information entered by the user,

[0851] [Means for generating necessary documents based on classified information,

[0852] [Means for analyzing the input content, identifying related items, and performing calculations,

[0853] [Means for providing information and calculation results to users,

[0854] [Means for receiving questions from users and generating answers using natural language processing technology,

[0855] [Means for notifying users of necessary documents and procedures,

[0856] [Means for detecting economic transactions and automatically assigning them to relevant classifications,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] [Means for verifying that the generated document conforms to a predetermined format] The system according to claim 1.

[0860] (Claim 3)

[0861] [A means of providing generated information and answers to users in real time, according to claim 1.

[0862] "Example 2 of combining an emotion engine"

[0863] (Claim 1)

[0864] [Means for receiving and classifying income information entered by the user,

[0865] [Means for generating necessary data records based on classified income information,

[0866] [Means for analyzing input expense information, identifying related expense items, and calculating,

[0867] [Means for detecting the user's psychological state using a behavioral analysis engine and optimizing the operation procedure accordingly,

[0868] [Means for receiving user questions and generating answers using natural language processing technology,

[0869] [Means for sending notifications to users regarding necessary information and procedures,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] [Means for confirming that the format of the generated data record conforms to a predetermined standard] The system according to claim 1.

[0873] (Claim 3)

[0874] [The system according to claim 1, which provides the generated data records and responses to the user immediately.

[0875] "Application example 2 when combining with an emotional engine"

[0876] (Claim 1)

[0877] [A module that receives income data entered by the user and classifies it,

[0878] [A module that generates necessary tax documents based on classified income data,

[0879] [A module means that analyzes the input expenditure data, identifies and calculates related expenditure items,

[0880] [A module that provides tax data and calculation results to users,

[0881] [A module that receives user questions and generates responses using natural language processing technology,

[0882] [A module that notifies users of reminders regarding necessary documents and procedures,

[0883] [A module means that analyzes the user's emotional state and adjusts the tone of operation suggestions and responses based on those emotions,

[0884] A system that includes this.

[0885] (Claim 2)

[0886] A system according to claim 1, which includes a module for generating tax documents to verify that the generated documents conform to a specified format.

[0887] (Claim 3)

[0888] A module for providing generated tax data and responses to the user immediately, according to claim 1. [Explanation of Symbols]

[0889] 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 receiving and classifying income information entered by users, A means of generating the necessary tax documents based on classified income information, A means for analyzing the entered expense information, identifying and calculating related expense items, Means of providing users with tax information and calculation results, A means for receiving questions from users and generating answers using natural language processing technology, A means of notifying users of necessary documents and procedures, A system that includes this.

2. The system according to claim 1, which provides a means for confirming that the generated tax documents conform to a predetermined format.

3. The system according to claim 1, which provides generated tax information and answers to users in real time.

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