System

Abstract

To provide a system.SOLUTION: A system includes: means for acquiring information inputted by a user; means for generating a form of a predetermined language using a generative AI model based on the information; means for translating the generated form into a language different from the predetermined language; and means for performing error check on whether the content of the generated form is appropriate or not based on the rule defined beforehand.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] When completing documents at city hall, language issues, missing documents, and errors often require resubmission, resulting in a poor experience for citizens using public services. [Means for solving the problem]

[0005] The system provides a means for automatically generating documents required by city hall, multi-language support, and automatic error checking. This system uses AI to understand the information required by the user and automatically generate the necessary forms. It also points out missing parts and errors in documents in real time, eliminating the need for resubmissions. [Brief explanation of the drawings]

[0006] [Figure 1]1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] One aspect of the present invention is a system that includes a means for automatically generating documents required by city hall, a means for multi-language support, and a means for automatic error checking. Specifically, AI understands the information required by the user and automatically generates the required form. For example, when creating an application form required by city hall, the user inputs the required information (e.g., name, address, application details, etc.), and the AI ​​understands the information and automatically generates the appropriate form.

[0029] "Example 2"

[0030] Additionally, aspects of the present invention provide multi-language support. Specifically, regardless of the language used by the user, the system will understand that language and generate the appropriate form. For example, if the user uses English, the system will understand the information in English and generate an English form.

[0031] "Example 3"

[0032] Furthermore, aspects of the present invention provide an automated error checking mechanism. Specifically, the system identifies missing or incorrect documents in real time, eliminating the need for resubmission. For example, if a user has omitted a portion of an application form, the system will point out the missing portion and prompt the user to correct it.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user enters the required information into the system (e.g., name, address, application details, etc.).

[0036] Step 2: AI understands the information provided by the user and automatically generates the appropriate form.

[0037] Step 3: The generated form is presented to the user for correction and confirmation if necessary.

[0038] "Example 2"

[0039] Step 1: Enter your preferred language into the system.

[0040] Step 2: The system understands the user's language and generates the appropriate form for that language.

[0041] Step 3: The generated form is presented to the user for correction and confirmation if necessary.

[0042] "Example 3"

[0043] Step 1: The user submits the document to the system.

[0044] Step 2: The system checks the submitted documents for missing parts and errors in real time.

[0045] Step 3: If an error is detected, the system notifies the user and prompts them to correct it.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] Creating documents required by city hall is time-consuming and error-prone for users. Furthermore, the complexity increases when multilingual support is required. This often leads to users wasting time and effort by having to resubmit documents. An efficient system to solve these problems is needed.

[0049] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0050] In this invention, the server includes a means for a user to input necessary information, a means for analyzing the input information, a means for automatically generating documents based on the analysis results, a means for providing the generated documents in multiple languages, and a means for performing error checks on the generated documents. This allows users to easily create the necessary documents and provides them in multiple languages, making them usable across language barriers. Furthermore, error checks can eliminate the need for resubmission.

[0051] "User" refers to an individual or organization that uses the system to prepare the necessary documents at City Hall.

[0052] "Means for inputting information" refers to the interface that allows users to input necessary information such as name, address, and application details into the system.

[0053] "Means for analyzing information" refers to technologies, such as generative AI models, used to analyze input information and generate appropriate documents.

[0054] "Means for automatically generating documents" refers to a function that automatically creates the necessary documents based on the analyzed information.

[0055] "Means for providing in multiple languages" refers to a technology for translating the generated document into multiple languages ​​and providing it to the user.

[0056] "Means for error checking" refers to the function of checking the accuracy and appropriateness of the input content of generated documents and detecting errors.

[0057] "Generative AI model" refers to the artificial intelligence technology used to analyze user-entered information and generate appropriate documents.

[0058] "Means for verifying the existence of an address" refers to technology for verifying whether the entered address actually exists.

[0059] "Error check rules" refer to predefined criteria and conditions for verifying the appropriateness of application content.

[0060] This invention is a system for efficiently creating documents required by city hall. The system allows users to input the necessary information, analyzes that information, automatically generates appropriate documents, provides them in multiple languages, and also has the ability to check for errors.

[0061] Hardware and software used

[0062] Hardware

[0063] Server: A central processing unit for analyzing information, generating documents, translating into multiple languages, and checking for errors.

[0064] Terminal: The device (e.g., computer, smartphone) where a user enters information and reviews the resulting documents.

[0065] software

[0066] Generative AI model: An artificial intelligence technology (e.g., GPT-4®) used to analyze user-entered information and generate appropriate documents.

[0067] Translation API: A service for translating generated documents into multiple languages ​​(e.g., Google® Translate API).

[0068] Map API: A service that checks the existence of an entered address (e.g., Google Maps API).

[0069] Program processing

[0070] Enter user information

[0071] The user accesses the system's web interface and enters the necessary information, such as name, address, application details, etc. For example, the user enters "Taro Tanaka, Shinjuku Ward, Tokyo, application for copy of resident registration card."

[0072] Sending information

[0073] The device sends the information entered by the user to the server in JSON format. The data sent is in the following format:

[0074] json

[0075] {

[0076] "name": "Taro Tanaka",

[0077] "address": "Shinjuku-ku, Tokyo",

[0078] "application_content": "Application for a copy of residence certificate"

[0079] }

[0080] Analysis of information

[0081] The server inputs the received JSON data into a generative AI model (e.g., GPT-4), which analyzes the user's input and selects an appropriate application form template.

[0082] Generate a form

[0083] The server automatically generates an application form based on the analysis results obtained from the generative AI model. For example, it generates a form containing the necessary fields for "application for a copy of resident registration."

[0084] Multilingual support

[0085] The server translates the generated Japanese form into English and Spanish using the Google Translate API. The translated form is then provided in multiple languages, as follows:

[0086] Japanese: Application for a copy of resident registration

[0087] English: Application for a Copy of Resident Certificate

[0088] Spanish: Solicitud de Copia del Certificado de Residencia

[0089] Error Checking

[0090] The server uses the Google Maps API to verify the existence of the entered address and checks the validity of the application based on predefined rules, for example, generating an error message if the address does not exist or if the application is invalid.

[0091] Form submission

[0092] The server sends the form after error checking to the terminal. The user can review the form provided through the terminal and make corrections as necessary. For example, if the user corrects their address, the form will be checked for errors again.

[0093] Specific examples

[0094] Example 1: When a user creates an application form in Japanese

[0095] 1. The user accesses the system and enters their name, address, and application details in Japanese.

[0096] 2. The server receives the input information and analyzes it using a generative AI model (e.g., GPT-4).

[0097] 3. The server automatically generates a Japanese application form based on the analysis results.

[0098] 4. The server also translates the generated form into English using the Google Translate API.

[0099] 5. The server uses the Google Maps API to verify the existence of the address and perform other error checking.

[0100] 6. The server provides the completed error-checked form to the user.

[0101] Example 2: Example of a prompt statement

[0102] "A user enters their name, address, and application details to fill out an application form at city hall. Based on this information, please automatically generate the appropriate form and provide it in multiple languages. Please also check the input for errors."

[0103] In this way, a system is realized that allows users to easily create the documents required at city hall.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Step 1:

[0106] The user accesses the system's web interface and enters the necessary information, such as name, address, and application details. The entered information is sent from the terminal to the server. The input data is text information, such as name, address, and application details.

[0107] Step 2:

[0108] The device sends the information entered by the user to the server in JSON format. The data sent is in the following format:

[0109] json

[0110] {

[0111] "name": "Taro Tanaka",

[0112] "address": "Shinjuku-ku, Tokyo",

[0113] "application_content": "Application for a copy of residence certificate"

[0114] }

[0115] The server receives this JSON data.

[0116] Step 3:

[0117] The server inputs the received JSON data into a generative AI model (e.g., GPT-4). The generative AI model analyzes the user's input and selects an appropriate application form template. As a result of the analysis, an application form template containing the required fields is generated.

[0118] Step 4:

[0119] The server automatically generates an application form based on the analysis results obtained from the generative AI model. For example, a form containing the necessary fields for "application for a copy of resident registration" is generated. The generated form is customized based on the information entered by the user.

[0120] Step 5:

[0121] The server translates the generated Japanese form using a translation API (e.g., Google Translate API) to provide it in multiple languages. The translated form is provided in multiple languages, such as English and Spanish. For example, the Japanese "Application for a Copy of Resident Certificate" is translated into English "Application for a Copy of Resident Certificate."

[0122] Step 6:

[0123] The server performs automatic error checking on the generated form. It uses the Google Maps API to check whether the entered address exists. It also checks whether the application details are valid based on predefined rules. For example, it generates an error message if the address does not exist or if the application details are invalid.

[0124] Step 7:

[0125] The server sends the form after error checking to the terminal. The user can review the form provided through the terminal and make corrections as necessary. For example, if the user corrects their address, the form will be checked for errors again.

[0126] (Application example 1)

[0127] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0128] Autonomous vehicles require passengers to quickly and accurately prepare the necessary documents when they arrive at their destination. However, current systems require passengers to prepare the documents manually, which can lead to language barriers and errors. This can reduce passenger convenience and delay procedures at the destination. Therefore, a system is needed that automatically generates the necessary documents before passengers arrive at their destination and checks for errors in real time.

[0129] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0130] In this invention, the server includes means for automatically generating documents required by city hall, multi-language support means, automatic error checking means, means for automatically generating documents required by passengers in the infotainment system of the autonomous vehicle before they arrive at their destination, means for passengers to input required information using a smart device, and means for AI to generate appropriate documents based on the input information, thereby enabling required documents to be prepared quickly and accurately before passengers arrive at their destination.

[0131] "Means for automatically generating documents required by city hall" is a function that automatically generates various documents required by city hall based on information entered by the user.

[0132] "Multi-language support means" refers to a function that supports multiple languages ​​and translates information entered by the user into the appropriate language.

[0133] The "automatic error checking means" is a function that detects missing parts or errors in the generated document in real time and notifies the user.

[0134] An "autonomous vehicle infotainment system" is a system installed in an autonomous vehicle that provides information and entertainment to passengers.

[0135] The "means for automatically generating necessary documents before a passenger arrives at a destination" is a function for automatically generating necessary documents before a passenger arrives at a destination.

[0136] "Means for passengers to input necessary information using smart devices" refers to a function that allows passengers to input necessary information using devices such as smartphones and tablets.

[0137] "Means for AI to generate appropriate documents based on input information" refers to a function in which artificial intelligence analyzes the information input by passengers and generates appropriate documents based on that information.

[0138] A system for implementing this invention is configured as follows: First, a server includes means for automatically generating documents required by city hall, means for multi-language support, means for automatic error checking, means for automatically generating documents required by passengers in an infotainment system of an autonomous vehicle before they arrive at their destination, means for passengers to input required information using a smart device, and means for AI to generate appropriate documents based on the input information.

[0139] Hardware and Software Configuration

[0140] Hardware: Autonomous vehicle infotainment systems, smartphones, tablets, touchscreens

[0141] Software: Python, Google Translate API, Langdetect library, generative AI model

[0142] Data processing and calculation

[0143] 1. Language detection: The server detects the language of the text entered by the user using the smart device using the Langdetect library.

[0144] 2. Translation: If necessary, translate the text into the desired language using the Google Translate API.

[0145] 3. Form generation: The server automatically generates the required document form based on the information entered by the user. It uses a generative AI model to analyze the input information and generate the appropriate document.

[0146] 4. Error checking: The server detects any missing parts or errors in the generated document in real time and notifies the user.

[0147] Specific examples

[0148] For example, to generate immigration documents required for a passenger visiting Japan for tourism purposes, the following prompt statement could be used:

[0149] Example prompt sentence:

[0150] Enter your user information:

[0151] Name: Yamada Taro

[0152] Address: Shinjuku Ward, Tokyo

[0153] Purpose: Sightseeing

[0154] By inputting this prompt into a generative AI model, the necessary documents are automatically generated. The server generates the appropriate documents based on the information entered by the user and performs error checking. This enables passengers to quickly and accurately prepare the necessary documents before arriving at their destination.

[0155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0156] Step 1:

[0157] The user enters the required information using a smart device.

[0158] Input: A user uses a smartphone or tablet to enter information such as name, address, and purpose.

[0159] Data processing: The entered information is sent to the server.

[0160] Output: The user's input information is saved on the server.

[0161] Step 2:

[0162] The server detects the language of the input information.

[0163] Input: Text information entered by the user.

[0164] Data Computing: Detect the language of the input text using the Langdetect library.

[0165] Output: Detected language information.

[0166] Step 3:

[0167] The server translates the input information as needed.

[0168] Input: User input and detected language information.

[0169] Data processing: Use Google Translate API to translate input information into the desired language.

[0170] Output: The translated text information.

[0171] Step 4:

[0172] The server generates the required document form based on the input information.

[0173] Input: User input information (including translated information).

[0174] Data Computing: Using generative AI models to analyze input information and automatically generate appropriate document forms.

[0175] Output: The form of the generated document.

[0176] Step 5:

[0177] The server checks the generated document for errors.

[0178] Input: The form of the generated document.

[0179] Data calculation: Detect missing parts and errors in documents in real time.

[0180] Output: The result of the error check (and an error message if there is an error).

[0181] Step 6:

[0182] The server notifies the user of the results of the error check.

[0183] Input: The result of the error check.

[0184] Data processing: Generate an error message and notify the user.

[0185] Output: The error message that is displayed to the user.

[0186] Step 7:

[0187] The user corrects the error and enters the information again.

[0188] Input: The user corrects the information based on the error message and re-enters it.

[0189] Data processing: The corrected information is sent to the server again.

[0190] Output: The corrected information stored on the server.

[0191] Step 8:

[0192] The server regenerates the document based on the corrected information and checks for errors.

[0193] Input: Corrected information.

[0194] Data calculation: Regenerate documents using the AI ​​model and check for errors.

[0195] Output: A final error-free document form.

[0196] Step 9:

[0197] The server provides the final document to the user.

[0198] Input: Final document form without errors.

[0199] Data Processing: Formatting the final document for delivery to the user.

[0200] Output: The final document provided to the user.

[0201] Example 2

[0202] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0203] In the previous system, users had to manually generate forms in the language they used, making it difficult to support multiple languages. Furthermore, the system lacked the functionality to point out missing or errors in the data entered by users in real time, which resulted in the hassle of having to resubmit the form.

[0204] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for detecting the language used by the user, means for generating an appropriate form based on the detected language, means for transmitting the generated form to the user's terminal, means for receiving and processing data entered by the user, and means for transmitting the processing result to the user's terminal. This makes it easy to support multiple languages ​​and makes it possible to point out missing parts and errors in data entered by the user in real time.

[0205] "User" refers to any individual or entity that uses the System.

[0206] "Language" refers to the natural language used by the user, including English, Japanese, Spanish, and the like.

[0207] "Means for detecting" refers to technical means for identifying the language used by a user, including natural language processing techniques.

[0208] "Form" means an electronic form for a user to enter required information.

[0209] "Generating means" refers to the technical means for automatically generating the appropriate form based on the identified language.

[0210] "Means for sending" refers to the technical means for sending the generated form and processing results to the user's terminal.

[0211] "Terminal" refers to an electronic device used by a user to access the system, including a personal computer, smartphone, tablet, etc.

[0212] "Means for receiving" refers to the technical means by which the server receives the data entered by the user.

[0213] "Processing means" refers to the technical means for analysing received data and producing the required result.

[0214] A "missing portion" refers to a portion where information that should be entered by the user is missing.

[0215] "Error" refers to an error in the data entered by the user.

[0216] "Real-time" refers to processing occurring immediately as the user enters data.

[0217] "Resubmission" refers to the act of a user correcting errors or omissions and then sending the data again.

[0218] This invention is a system that automatically detects the language used by the user, generates an appropriate form, and provides it to the user. The system consists of three main elements: a server, a terminal, and a user.

[0219] The server uses natural language processing technology to detect the language used by the user, specifically using services such as the Google Cloud Natural Language API or the Microsoft® Azure® Text Analytics API. The server analyzes the user's input data and identifies the language used.

[0220] The server then generates the appropriate form based on the identified language. The server retrieves a template from the database that corresponds to the user's language and generates the form based on that template. For example, if the user speaks English, the server creates the form using the English template.

[0221] The generated form is sent from the server to the user's device. The server transmits data using the HTTP protocol, specifically through a RESTful API. The device parses the received form data and displays it in a user interface. The device renders the form using a front-end framework such as React or Vue.js.

[0222] The user enters the necessary information into the displayed form and presses the submit button. The device then generates an HTTP request again to send the data entered by the user to the server. The server processes the received data and generates the necessary results, such as saving it in a database or linking it to other services.

[0223] The processing results are sent from the server to the terminal, which then displays them to the user, allowing the user to check whether their input has been processed correctly.

[0224] As a concrete example, consider the case where a user inputs "I need a registration form" in English. The terminal sends this input data to the server, which analyzes the input data and determines that the user is using English. The server generates a registration form using an English template and sends the generated English registration form to the terminal. The terminal displays the received English registration form to the user, who enters the required information and submits it. The server processes the received data, generates a result, and sends it to the terminal, which then displays the result to the user.

[0225] An example of a prompt is as follows:

[0226] "Parse data entered by the user in English and generate an English form."

[0227] "Please parse the data entered by the user in Japanese and generate a form in Japanese."

[0228] In this way, the system can generate and present the appropriate form to the user regardless of the language the user uses.

[0229] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0230] Step 1:

[0231] The user selects or types a language.

[0232] Input: The language used by the user (e.g. English, Japanese)

[0233] How it works: The user selects the language they want to use on the system interface or enters it directly.

[0234] Output: Selected or entered language information

[0235] Step 2:

[0236] The terminal sends the user's input to the server.

[0237] Input: Language information selected or entered by the user

[0238] Operation: The terminal sends the language information selected or entered by the user to the server by generating an HTTP POST request.

[0239] Output: Language information sent to the server

[0240] Step 3:

[0241] The server detects the user's language.

[0242] Input: Language information sent to the server

[0243] How it works: The server analyzes the received data and determines the language used by the user, specifically using natural language processing techniques.

[0244] Output: Identified language information

[0245] Step 4:

[0246] The server generates the appropriate form.

[0247] Input: Identified language information

[0248] How it works: The server generates the appropriate form based on the language identified, by retrieving the corresponding template from the database and creating the form based on that template.

[0249] Output: The generated form data

[0250] Step 5:

[0251] The server sends the generated form to the terminal.

[0252] Input: Generated form data

[0253] How it works: The server sends the generated form data to the terminal, specifically via a RESTful API using the HTTP protocol.

[0254] Output: Form data sent to the terminal

[0255] Step 6:

[0256] The terminal displays the form to the user.

[0257] Input: Form data sent to the terminal

[0258] What it does: The terminal parses the received form data and displays it in a user interface, specifically by rendering the form using a front-end framework such as React or Vue.js.

[0259] Output: The form displayed to the user

[0260] Step 7:

[0261] The user fills in the required information in the form and submits it.

[0262] Input: Information entered by the user (e.g., name, email address)

[0263] How it works: The user enters the required information into the displayed form and presses the submit button.

[0264] Output: The information entered

[0265] Step 8:

[0266] The terminal sends the input data to the server.

[0267] Input: Information entered

[0268] Operation: The terminal generates an HTTP POST request to send the data entered by the user to the server.

[0269] Output: The input data sent to the server

[0270] Step 9:

[0271] The server processes the input data and produces a result.

[0272] Input: Input data sent to the server

[0273] Operation: The server analyzes the received data and generates the necessary results, such as storing them in a database or connecting to other services.

[0274] Output: Generated result data

[0275] Step 10:

[0276] The server sends the results to the terminal.

[0277] Input: Generated result data

[0278] Operation: The server sends the generated result data to the terminal. Specifically, it sends the data in JSON format again via the RESTful API.

[0279] Output: Result data sent to the terminal

[0280] Step 11:

[0281] The terminal displays the results to the user.

[0282] Input: Result data sent to the terminal

[0283] How it works: The device parses the result data received from the server and displays it in the user interface. Specifically, it uses React to render the results.

[0284] Output: The result displayed to the user

[0285] (Application example 2)

[0286] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0287] With the previous system, it was difficult to automatically generate the appropriate form according to the user's language, which led to a poor user experience, especially in environments where multilingual support was required. Furthermore, the system lacked the functionality to point out missing or incorrect documents in real time, which often required users to resubmit documents.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an automatic document generation means, a multi-language support means, an automatic error check means, a means for detecting the user's input language, and a means for generating an appropriate form based on the detected language. This makes it possible to automatically generate an appropriate form according to the language used by the user, and by pointing out missing parts and errors in the document in real time, it becomes possible to eliminate the need for resubmission.

[0289] "Automatic document generation means" is a function that automatically creates appropriate documents and forms based on the information required by the user.

[0290] "Multi-language support means" refers to a function that supports multiple languages ​​used by users and provides appropriate information in each language.

[0291] "Automatic error checking means" is a function that detects missing parts and errors in documents in real time and points them out to the user.

[0292] A "means for detecting the user's input language" is a function that automatically identifies the language of text entered by the user.

[0293] The "means for generating an appropriate form based on the detected language" is a function that automatically generates an appropriate form in a language that the user can easily understand, depending on the detected language.

[0294] A system for implementing the present invention includes means for automatically generating documents, means for multi-language support, means for automatic error checking, means for detecting a user's input language, and means for generating an appropriate form based on the detected language.

[0295] The server uses a language detection library (e.g., langdetect) to automatically identify the language of the text entered by the user. If the text entered by the user is Japanese, it generates a Japanese form, and if it is English, it generates an English form. This process involves using Google's translation API (googletrans library) to translate the text if necessary.

[0296] Specifically, if a user types "search for products" on a smartphone, the server receives this input and uses a language detection library to identify that it is in Japanese. It then generates a Japanese form and provides it to the user, allowing the user to search for products in their own language and proceed with the purchase process.

[0297] The server also uses automated error checking to detect missing or incorrect parts of the generated form in real time and notify the user, saving the user the trouble of having to resubmit the form.

[0298] The hardware used is a smartphone, and the software is Python, the langdetect library, and the googletrans library.

[0299] For example, if a user types "Search for products", a Japanese form will be generated. An example of this prompt is:

[0300] If a user types "Search for products", generate a form in Japanese.

[0301] In this way, it is possible to automatically generate the appropriate form according to the language used by the user, and by pointing out missing parts or errors in the document in real time, it is possible to eliminate the need to resubmit the form.

[0302] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0303] Step 1:

[0304] A user uses a smartphone to input text, for example, "Search for a product." This input text is sent to the system.

[0305] Step 2:

[0306] The server analyzes the received input text using a language detection library (langdetect) to identify the language of the input text. The input is the user's text, and the output is the identified language (Japanese in this case).

[0307] Step 3:

[0308] The server generates an appropriate form based on the identified language, where templates for form generation are available and a template is selected depending on the language, the input is the identified language, and the output is the generated form.

[0309] Step 4:

[0310] The server sends the generated form to the user's smartphone, where the user can view the form displayed in their own language. The input is the generated form, and the output is the form displayed on the user's smartphone.

[0311] Step 5:

[0312] The user fills in the form and presses the submit button. The entered data is sent to the server. The input is the data the user entered into the form, and the output is the data sent to the server.

[0313] Step 6:

[0314] The server uses automatic error checking to detect missing or erroneous data in real time. The input is the data sent by the user, and the output is any detected errors.

[0315] Step 7:

[0316] The server notifies the user of the detected error information. The user receives instructions for correcting the error, and can correct the form again and submit it. The input is the detected error information, and the output is the error information notified to the user.

[0317] Step 8:

[0318] The user corrects the errors and submits the form again. The server receives the data again and checks for errors. If there are no errors, the data is processed successfully. The input is the corrected data, and the output is the successfully processed data.

[0319] In this way, an appropriate form is automatically generated according to the language used by the user, and error checking is performed in real time.

[0320] Example 3

[0321] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0322] Conventional document submission systems required users to manually check and correct missing or incorrect documents, resulting in time-consuming resubmissions. Furthermore, they lacked multilingual support, making them difficult for users who speak different languages. Furthermore, they lacked the technology to accurately analyze document content, resulting in low error detection accuracy.

[0323] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0324] In this invention, the server includes an automatic document generation means, a multilingual support means, an automatic error check means, an optical character recognition means, an analysis means using a generative AI model, and a real-time notification means. This allows missing parts and errors in documents submitted by users to be detected in real time and prompt corrections to be made. Multilingual support also makes it easy for users who speak different languages ​​to use the system. Furthermore, analysis using a generative AI model allows for highly accurate analysis of the document contents, improving the accuracy of error detection.

[0325] "Automatic document generation means" is a function that automatically generates the necessary forms based on the information required by the user.

[0326] "Multilingual support means" refers to a function that provides system functions and interfaces in multiple languages ​​to users who speak different languages.

[0327] "Automatic error checking means" is a function that detects missing parts or errors in submitted documents in real time and notifies the user.

[0328] "Optical character recognition means" is a technology for converting uploaded documents into text data.

[0329] "Analysis means using a generative AI model" is a function that uses a generative AI model to analyze text data and understand the contents of a document.

[0330] "Real-time notification means" is a function that immediately notifies the user of detected missing parts or errors.

[0331] This invention is a system that detects missing parts and errors in documents submitted by users in real time and prompts them to correct them quickly. The system includes an automatic document generation means, a multilingual support means, an automatic error check means, an optical character recognition means, an analysis means using a generative AI model, and a real-time notification means.

[0332] First, the user accesses the system interface using a terminal and uploads documents such as application forms. The documents to be uploaded are in PDF or image format. The server receives the documents uploaded by the user and temporarily stores them on the server.

[0333] The server then uses optical character recognition (e.g., Tesseract OCR) to convert the uploaded document into text data, which converts images and PDF documents into parseable text data.

[0334] The server uses a generative AI model (e.g., OpenAI (registered trademark) GPT-4) to analyze the converted text data. The goal of the analysis is to understand the content of the document and identify gaps and errors. Examples of prompts to input to the generative AI model include the following:

[0335] Analyze the application submitted by the user to detect missing parts and errors. Analyze the following text data:

[0336] [Text data]

[0337] The server uses the results of the generative AI model's analysis to detect missing parts and errors in the document, such as missing required fields or incorrect formatting.

[0338] Any missing or errors detected are notified to the user using real-time notification methods. Notifications are displayed in real time on the system interface, and can also be sent by email or other means if necessary.

[0339] For example, suppose a user uploads a mortgage application. The application is missing the annual income field. When the user uploads the application, the server receives the document and converts it into text data using Tesseract OCR. Next, it analyzes the text data using a generative AI model (e.g., OpenAI GPT-4) and detects that the annual income field is missing. Based on this information, the server notifies the user, "The annual income field is missing. Please correct it." The user receives this notification, fills in the annual income field, and uploads the application again.

[0340] In this way, users can quickly correct missing parts and errors in documents, eliminating the need to resubmit them. Multilingual support also makes it easy for users who speak different languages ​​to use the system. Furthermore, analysis using a generative AI model enables highly accurate analysis of document content, improving the accuracy of error detection. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[0341] Step 1:

[0342] User uploads document

[0343] Users access the system interface using a terminal and upload documents such as application forms. The input is documents in PDF format or image format, and the output is the document data sent to the server.

[0344] Step 2:

[0345] The server receives the document

[0346] The server receives the document uploaded by the user and temporarily stores it in the server. The input is the document data sent by the user, and the output is the document data stored in the server.

[0347] Step 3:

[0348] The server converts the document into text data using OCR software.

[0349] The server converts the uploaded document into text data using optical character recognition (e.g., "Tesseract OCR"). The input is the document data stored on the server, and the output is text data. Specifically, the OCR software analyzes the document image and extracts the text information.

[0350] Step 4:

[0351] The server analyzes the text data using a generative AI model

[0352] The server uses a generative AI model (such as OpenAI GPT-4) to analyze the converted text data. The input is the text data, and the output is the analysis result. Specifically, the generative AI model analyzes the text data based on the prompt and understands the content of the document.

[0353] Step 5:

[0354] The server detects missing parts and errors based on the analysis results.

[0355] The server detects missing parts and errors in documents based on the analysis results of the generative AI model. The input is the analysis results, and the output is a list of missing parts and errors. Specifically, it collates the analysis results and identifies missing required fields and formatting errors.

[0356] Step 6:

[0357] The server notifies the user of any missing parts or errors

[0358] The server notifies the user of any missing parts or errors that it detects. The input is a list of missing parts or errors, and the output is a notification message to the user. Specifically, the server displays a notification in real time on the system interface and notifies the user by email or other means if necessary.

[0359] Step 7:

[0360] The user corrects the document and resubmits it

[0361] The user receives a notification from the server and corrects any missing parts or errors that have been pointed out. After the corrections are complete, the user uploads the document again and resubmits it. The input is the notification message from the server, and the output is the corrected document data. Specifically, the user corrects the document and uploads it to the system again.

[0362] (Application example 3)

[0363] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0364] The existing system lacked the ability to automatically generate documents required by city hall or to support multiple languages. Furthermore, it lacked the functionality to point out missing or incorrect documents in real time, forcing users to go through the trouble of resubmitting them. Furthermore, there was a problem with missing or incorrect information being easily input when entering electronic payment information, which led to frequent payment errors. A system that could solve these issues was needed.

[0365] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0366] In this invention, the server includes a means for automatically generating documents required by the city hall, a multi-language support means, an automatic error checking means, and a means for pointing out missing or error parts in electronic payment information in real time and prompting the user to correct them. This makes it possible to point out missing or error parts in documents in real time and eliminate the need for resubmission. Furthermore, when inputting electronic payment information, missing or error parts are pointed out in real time and the user is prompted to correct them, thereby reducing payment errors.

[0367] A "city hall" is an administrative agency of a local government and a facility that provides various administrative services to citizens.

[0368] An "automatic document generation means" is a system that has the function of automatically creating the necessary documents and forms based on the information required by the user.

[0369] "Multi-language support means" means a system that supports multiple languages ​​and has the ability to provide information in the language selected by the user.

[0370] An "automatic error checking means" is a system that has the function of detecting missing parts or errors in documents or input information in real time and prompting the user to make corrections.

[0371] "Electronic Payment Information" refers to information such as credit card information, address, and name required for online payments.

[0372] A "missing portion" refers to a portion where necessary information has not been entered.

[0373] An "error" is when the information entered is incorrect or out of format.

[0374] "Real-time" refers to immediate processing and feedback as users input information.

[0375] "User" refers to any individual or entity that uses the System.

[0376] "Encouraging correction" means pointing out any errors or omissions in the information entered to the user and asking them to re-enter the correct information.

[0377] A system for implementing this invention includes a server, a user terminal, and a network. The server includes a means for automatically generating documents required by the city hall, a multi-language support means, an automatic error checking means, and a means for pointing out missing or errors in electronic payment information in real time and prompting the user to correct them.

[0378] A user terminal is a device such as a smartphone, tablet, or PC that provides an interface for users to input information. Once the user uses the terminal to input the required information, the information is sent to the server.

[0379] The server first receives the information entered by the user and then uses an automated document generation method to automatically create the necessary documents and forms, using a generative AI model to analyze the user's input and generate the appropriate documents.

[0380] Multi-language support is then used to provide information in the user's language of choice, thereby accommodating users who speak different languages.

[0381] Additionally, automated error checking measures are used to detect missing or incorrect information entered by the user in real time, such as checking that credit card numbers, expiration dates, security codes, names, addresses, etc. If an error is detected, the server provides immediate feedback to the user to prompt them to make corrections.

[0382] As a concrete example, consider the case where a user leaves out part of the card number when entering credit card information. In this case, the server displays an error message saying "The credit card number is invalid" and asks the user to re-enter the correct information.

[0383] Example prompts to input to a generative AI model:

[0384] Write a program that checks the credit card information entered by the user and points out any missing or incorrect information in real time. Check the following fields: credit card number, expiration date, security code, name, and address. If there are any errors in each field, add the errors to a list and provide feedback to the user.

[0385] This system can point out missing or errors in documents in real time, eliminating the need for resubmission. It can also point out missing or errors in electronic payment information entry in real time and prompt users to correct them, reducing payment errors.

[0386] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0387] Step 1:

[0388] The user uses the terminal to enter the required information.

[0389] Input: Information entered by the user through the device interface (e.g., credit card number, expiration date, security code, name, address).

[0390] Output: The entered information is sent from the terminal to the server.

[0391] Step 2:

[0392] The server analyzes the received information and automatically creates the necessary documents and forms using an automatic document generation means.

[0393] Input: User input sent from the device.

[0394] Data processing: Using generative AI models to analyze user input and generate appropriate documents.

[0395] Output: The generated documents or forms.

[0396] Step 3:

[0397] The server uses multi-language support to provide information in the language selected by the user.

[0398] Input: User input and language selection.

[0399] Data processing: Translate information based on the selected language and provide it to the user.

[0400] Output: Information displayed in the user's language of choice.

[0401] Step 4:

[0402] The server uses automated error checking measures to detect missing or incorrect information entered by the user in real time.

[0403] Input: User input information.

[0404] Data processing: Use regular expressions and other validation algorithms to detect missing or error information in input.

[0405] Output: A list of detected errors and omissions.

[0406] Step 5:

[0407] The server provides feedback to the user to prompt them to correct any errors or omissions it detects.

[0408] Input: A list of detected errors and omissions.

[0409] Data processing: Generate an error message and display it to the user.

[0410] Output: The error message that is displayed to the user.

[0411] Step 6:

[0412] The user corrects the information based on the error message and re-enters it.

[0413] Input: User-modified information.

[0414] Output: The corrected information is sent to the server again.

[0415] Step 7:

[0416] The server parses the information again to ensure there are no errors.

[0417] Input: Corrected information.

[0418] Data processing: Validate input information again using regular expressions or other validation algorithms.

[0419] Output: If there are no errors, processing is complete. If there are errors, go back to step 5 again.

[0420] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0421] "Example 1"

[0422] One embodiment of the present invention provides a system incorporating an emotion engine. This system recognizes a user's emotions and adjusts its operation according to the user's emotional state. Specifically, if the system recognizes that the user is feeling stressed, it adjusts the operation of the automatic generation means and automatic error checking means to reduce the user's stress. For example, the system may change the way error messages are displayed to a gentler tone or automatically generate the necessary documents more smoothly.

[0423] "Example 2"

[0424] The emotion engine also recognizes users' feelings of joy and satisfaction and uses that information to improve system performance. For example, if the system recognizes that a user is satisfied with the automated generation of a particular form, it can learn how to generate that form and improve form generation in similar situations.

[0425] "Example 3"

[0426] Furthermore, the emotion engine also adjusts the operation of the multi-language support measures according to the user's emotional state. For example, if the system recognizes that the user is confused, it will strengthen support in the user's native language. This allows the user to receive support in their own language, clear up their confusion, and smoothly proceed with completing the necessary documents.

[0427] The processing flow of each embodiment will be described below.

[0428] "Example 1"

[0429] Step 1: The system recognizes the user's emotions using an emotion engine.

[0430] Step 2: If the emotion engine recognizes the user's stress, the system adjusts the behavior of the automatic generation and error checking measures.

[0431] Step 3: Specifically, we will change the way error messages are displayed to a gentler tone and make the automatic generation of necessary documents smoother.

[0432] "Example 2"

[0433] Step 1: The emotion engine recognizes the user's joy or satisfaction.

[0434] Step 2: If the user recognizes that they are happy with the auto-generation of a particular form, the system learns how to generate that form.

[0435] Step 3: Use the learned information to improve form generation in similar situations.

[0436] "Example 3"

[0437] Step 1: The emotion engine adjusts the behavior of the multi-language support means according to the user's emotional state.

[0438] Step 2: If the system recognizes that the user is confused, it will provide more support in the user's native language.

[0439] Step 3: This allows users to receive support in their own language, clearing up any confusion and helping them complete the necessary paperwork.

[0440] Example 1

[0441] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0442] Creating documents required by city hall is a cumbersome and time-consuming process for users. Furthermore, when multilingual support is required or when document error checking is required, the process becomes even more time-consuming. Furthermore, users may find it difficult to operate the system in stressful situations. An efficient system that can solve these problems is needed.

[0443] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes an automatic generation means, a multilingual support means, an automatic error check means, an emotion recognition means, a user information input means, an information transmission means, and a feedback provision means. This makes it possible to quickly and accurately automatically generate documents required by the user, support multiple languages, perform error checks, and further adjust the operation of the system according to the user's emotional state.

[0444] "Automatic generation means" is a function that automatically generates necessary documents and forms based on information entered by the user.

[0445] "Multilingual support means" is a function that translates generated documents and forms into multiple languages ​​and provides them in the language selected by the user.

[0446] "Automatic error checking means" is a function that automatically detects missing parts and errors in generated documents and forms and points them out in real time.

[0447] "Emotion recognition means" is a function that analyzes the user's emotional state and adjusts the system's operation according to that emotional state.

[0448] "User information input means" is a function that provides an interface for the user to input necessary information.

[0449] "Information transmission means" is a function that transmits information entered by the user to the server.

[0450] The "feedback providing means" is a function that displays information and error messages received from the server to the user and provides necessary feedback.

[0451] MODE FOR CARRYING OUT THE INVENTION

[0452] The present invention is a system for automatically generating documents required by city hall, and aims to quickly and accurately generate the necessary documents and forms based on information entered by the user. This system includes an automatic generation means, a multilingual support means, an automatic error check means, an emotion recognition means, a user information input means, an information transmission means, and a feedback provision means.

[0453] Hardware and software used

[0454] Hardware: The device (e.g., PC, smartphone, tablet) through which the user enters information and the server that processes the information.

[0455] Software: Generative AI models (e.g., OpenAI's GPT-4), translation software (e.g., Google Translate API), emotion recognition AI models, and rule-based error-checking algorithms.

[0456] Program processing

[0457] 1. Enter your user information

[0458] The user uses the terminal to enter the necessary information (e.g., name, address, application details, etc.).

[0459] The terminal temporarily stores the entered information and prepares it for the next processing step.

[0460] 2. Transmission of information

[0461] The device sends the saved user information to the server.

[0462] The server analyzes the received information and converts it into the required data format.

[0463] 3. Information Understanding and Automatic Form Generation

[0464] The server generates prompt sentences to input the received information into the generative AI model.

[0465] The server sends prompts to the generative AI model, which then automatically generates the appropriate form.

[0466] The generative AI model generates the required document form based on the prompt sentence and returns it to the server.

[0467] 4. Multilingual support

[0468] The server checks the user's language preference.

[0469] The server translates the generated form using translation software to make it multilingual.

[0470] The server sends the translated form to the terminal.

[0471] 5. Automatic Error Checking

[0472] The server validates the entered information and generated forms with automated error checking.

[0473] If an error is detected, the server generates an error message and sends it to the terminal.

[0474] 6. Emotional engine for behavior adjustment

[0475] The server analyzes the user's emotional state using an emotion recognition AI model.

[0476] If the server detects that the user is stressed, it will change the tone of the error message to be gentler.

[0477] The server will make adjustments as necessary to smooth the form generation process.

[0478] 7. Providing Feedback

[0479] The terminal displays the final form and any error messages received from the server to the user.

[0480] The user checks the displayed information and corrects or re-enters it as necessary.

[0481] Specific examples

[0482] For example, consider the case where a user applies for a copy of their resident registration card at city hall. The user enters their name "Yamada Taro," their address "Shinjuku Ward, Tokyo," and the request for a copy of their resident registration card into their device. The device then sends this information to the server. The server then sends the following prompt to the generative AI model:

[0483] Generate a form for a user to apply for a copy of their resident registration card at city hall. The user's name is "Yamada Taro," their address is "Shinjuku-ku, Tokyo," and the request is for a copy of their resident registration card.

[0484] The generative AI model generates an application form for a copy of the resident registration certificate based on this prompt and returns it to the server. The server translates the form using the Google Translate API to make it multilingual and performs error checking. If an error is detected, the emotion engine recognizes the user's stress and generates a gentle error message. Finally, the device displays the generated form and error message to the user.

[0485] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0486] Step 1: Enter your user information

[0487] The user uses the terminal to enter the necessary information (e.g., name, address, application details, etc.).

[0488] Input: Information entered by the user (name, address, application details).

[0489] The terminal temporarily stores the entered information and prepares it for the next processing step.

[0490] Output: Saved user information.

[0491] Step 2: Submit your information

[0492] The device sends the saved user information to the server.

[0493] Input: Saved user information.

[0494] The server analyzes the received information and converts it into the required data format.

[0495] Output: Parsed user information.

[0496] Step 3: Understanding the information and automatically generating the form

[0497] The server generates prompt sentences to input the received information into the generative AI model.

[0498] Input: Parsed user information.

[0499] The server sends prompts to the generative AI model, which then automatically generates the appropriate form.

[0500] The generative AI model generates the required document form based on the prompt sentence and returns it to the server.

[0501] Output: The generated form.

[0502] Step 4: Multilingual support

[0503] The server checks the user's language preference.

[0504] Input: Generated form, user language preference.

[0505] The server translates the generated form using translation software to make it multilingual.

[0506] The server sends the translated form to the terminal.

[0507] Output: The translated form.

[0508] Step 5: Automatic error checking

[0509] The server validates the entered information and generated forms with automated error checking.

[0510] Input: translated form, user information.

[0511] If an error is detected, the server generates an error message and sends it to the terminal.

[0512] Output: Error message (if necessary).

[0513] Step 6: Adjusting behavior with the emotion engine

[0514] The server analyzes the user's emotional state using an emotion recognition AI model.

[0515] Input: The user's emotional state.

[0516] If the server detects that the user is stressed, it will change the tone of the error message to be gentler.

[0517] The server will make adjustments as necessary to smooth the form generation process.

[0518] Output: Adjusted error messages, smoother form generation process.

[0519] Step 7: Provide feedback

[0520] The terminal displays the final form and any error messages received from the server to the user.

[0521] Input: Final form, error messages.

[0522] The user checks the displayed information and corrects or re-enters it as necessary.

[0523] Output: User confirmation and correction information.

[0524] (Application example 1)

[0525] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0526] Document processing at city halls is cumbersome for users, and the process becomes even more complicated when multilingual support and error checking are insufficient. Furthermore, users often feel stressed, which reduces the efficiency of the process. A system that solves these issues and reduces the burden on users is needed.

[0527] 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. In this invention, the server includes an automatic generation means for documents required by the city hall, a multi-language support means, an automatic error check means, an emotion recognition means, an interface adjustment means, and an automatic document generation means. This enables the AI ​​to understand the information required by the user and automatically generate the necessary forms. In addition, by recognizing the user's emotional state and adjusting the system's operation according to that emotional state, it is possible to reduce user stress and improve the efficiency of procedures.

[0528] A "city hall" is an administrative agency of a local government and a facility that provides various administrative services to citizens.

[0529] "Automatic document generation means" is a system that has the function of automatically creating the necessary documents based on the information entered by the user.

[0530] "Multi-language support means" refers to a system that supports multiple languages ​​and has the function of providing services in the language selected by the user.

[0531] An "automatic error checking means" is a system that has the ability to detect missing parts and errors in documents in real time and point them out to the user.

[0532] An "emotion recognition means" is a system that has the function of recognizing the user's emotional state and adjusting the system's operation based on that information.

[0533] The "interface adjustment means" is a system that has the function of adjusting the system's user interface in accordance with the user's emotional state, thereby reducing the user's stress.

[0534] "AI" is an abbreviation for artificial intelligence, a technology that allows machines to imitate human intelligence and learn and reason.

[0535] A "form" refers to a form or document that allows a user to enter required information.

[0536] "Real-time" means that data processing and information provision are immediate.

[0537] "User" refers to any individual or entity that uses the System.

[0538] The system for implementing this invention includes a means for automatically generating documents required by city hall, a multi-language support means, an automatic error check means, an emotion recognition means, and an interface adjustment means. Specific embodiments of each means will be described below.

[0539] 1. Automatic document generation method

[0540] The server automatically creates the necessary documents based on the information entered by the user. Specifically, when the user enters information such as name, address, and application details through a smartphone application, the AI ​​understands the information and automatically generates the appropriate form. The FPDF library is used to generate the documents in PDF format.

[0541] 2. Multi-language support methods

[0542] The server supports multiple languages ​​and provides services in the language selected by the user. For example, if a user selects a language such as English, Spanish, or Chinese, the system will generate documents in that language and provide them to the user. This allows many users to use the system across language barriers.

[0543] 3. Automatic Error Checking Methods

[0544] The server detects missing or incorrect information in real time and notifies the user. Specifically, it checks each field on the document based on the information entered by the user, and immediately notifies the user if there are any missing or incorrect information. This saves the user the trouble of having to resubmit the document.

[0545] 4. Emotion recognition means

[0546] The server uses the smartphone camera to recognize the user's emotional state. Specifically, it analyzes the user's facial image using the OpenCV library and determines the user's emotions using an emotion recognition model (Transformers). This allows it to determine whether the user is feeling stressed.

[0547] 5. Interface Adjustment Methods

[0548] The server adjusts the system's user interface according to the user's emotional state obtained by the emotion recognition means. For example, if it determines that the user is feeling stressed, it changes the tone of the interface to a gentler one and makes error messages more friendly. This reduces the user's stress and improves the efficiency of the procedure.

[0549] Specific examples

[0550] The user opens the smartphone app and enters the required information (name, address, application details). The smartphone camera takes a photo of the user's face and performs emotion recognition. The tone of the interface is adjusted based on the emotion recognition results. A PDF application form is automatically generated based on the entered information and provided to the user.

[0551] Prompt Sentence Examples

[0552] The user opens the smartphone app and enters the required information (name, address, application details). The smartphone camera takes a photo of the user's face and performs emotion recognition. The tone of the interface is adjusted based on the emotion recognition results. A PDF application form is automatically generated based on the entered information and provided to the user.

[0553] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0554] Step 1:

[0555] The user opens the smartphone app and enters the required information (name, address, application details). The entered information is sent from the device to the server. The server receives this information and stores it in a database. The input data is text data such as name, address, and application details.

[0556] Step 2:

[0557] The server automatically generates documents based on the received information. Specifically, it uses a generative AI model to analyze the information entered by the user and automatically generate the appropriate form. It uses the FPDF library to generate the document in PDF format. The output is a PDF application form that reflects the user's information.

[0558] Step 3:

[0559] A user takes a facial image using a smartphone camera. The captured image is sent from the device to a server. The server receives the image and analyzes the user's emotional state using emotion recognition. Specifically, the server preprocesses the facial image using the OpenCV library and determines the emotion using an emotion recognition model (Transformers). The input is facial image data, and the output is the emotional state (e.g., stress, relaxation, etc.).

[0560] Step 4:

[0561] The server adjusts the interface based on the emotion recognition results. Specifically, if it determines that the user is feeling stressed, it changes the interface tone to a gentler one and makes error messages more friendly, thereby reducing the user's stress. The input is emotional state data, and the output is the adjusted interface settings.

[0562] Step 5:

[0563] The server provides the generated PDF application form to the user. Specifically, it sends the generated PDF to the user's device so that the user can download it. The user checks the provided application form and prints or submits it as necessary. The input is the generated PDF data, and the output is the PDF file sent to the user's device.

[0564] Example 2

[0565] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0566] Conventional automated document generation systems are sometimes unable to support the language used by users, and the systems are not improved to take into account user sentiment and feedback, resulting in a poor user experience and underperforming systems.

[0567] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0568] In this invention, the server includes an automatic document generation means, a multi-language support means, an automatic error check means, a sentiment analysis means, and a means for improving system performance based on user feedback, thereby enabling appropriate forms to be generated regardless of the language used by the user and improving system performance by taking into account the user's sentiment and feedback.

[0569] "Automatic document generation means" refers to a means that has the function of automatically generating appropriate documents and forms based on the information required by the user.

[0570] "Multi-language support means" means that the system has the ability to understand the language used by the user and generate documents and forms in the appropriate language, regardless of the language used by the user.

[0571] An "automated error checking means" is a means that has the function of checking in real time whether there are any missing parts or errors in generated documents or forms and notifying the user.

[0572] "Emotion analysis means" refers to means that has the function of analyzing user input and feedback and acquiring user emotional information.

[0573] "Means for improving system performance based on user feedback" refers to means that have the function of improving the system's algorithms and functions based on the acquired user emotional information and feedback, thereby improving performance from the next time onwards.

[0574] MODE FOR CARRYING OUT THE INVENTION

[0575] This invention is a system that automatically generates appropriate documents and forms regardless of the language used by the user, and improves the system's performance based on the user's feelings and feedback. Specific embodiments of this system are described below.

[0576] System configuration

[0577] The system consists of three main components: a server, a terminal, and a user. The server includes a means for automatic document generation, a means for multi-language support, a means for automatic error checking, a means for sentiment analysis, and a means for improving system performance based on user feedback.

[0578] Hardware and software used

[0579] The server uses the following hardware and software:

[0580] Natural language processing engine: Google Cloud Natural Language API

[0581] Template engine: Handlebars.js

[0582] Sentiment analysis engine: IBM Watson(R) Tone Analyzer

[0583] The terminal provides an interface for receiving user input and sending it to the server. The user accesses the system through the terminal and enters the required information.

[0584] Program processing

[0585] The server analyzes the information entered by the user and identifies the language used. Specifically, it uses the Google Cloud Natural Language API to analyze the entered text data. From the analysis results, it determines the language of the entered text.

[0586] The server then generates the appropriate documents and forms based on the identified language, using Handlebars.js to dynamically create forms containing the information the user is requesting.

[0587] The generated form is sent from the server to the terminal and displayed to the user, who then checks the displayed form and enters the required information.

[0588] When a user provides feedback in the form, the device sends the feedback to the server, which uses IBM Watson Tone Analyzer to analyze the user's feedback and obtain the user's emotional information.

[0589] Based on the acquired emotional information, the server learns to improve the system's performance. Specifically, it improves the form generation algorithm and reflects this in future form generation.

[0590] Specific examples

[0591] For example, if a user enters "I need a registration form for a new user" in English, the server processes it as follows:

[0592] 1. The server uses the Google Cloud Natural Language API to determine that the input text is in English.

[0593] 2. The server generates a registration form in English using Handlebars.js.

[0594] 3. The server sends the generated English registration form to the terminal.

[0595] 4. The terminal displays the received form to the user.

[0596] 5. The user provides feedback on the form's usability, saying "This form is very user-friendly."

[0597] 6. The device sends the user's feedback to the server.

[0598] 7. The server uses IBM Watson Tone Analyzer to recognize that the user is satisfied with the form.

[0599] 8. The server improves the form generation algorithm based on the acquired emotion information.

[0600] Example prompt sentence:

[0601] Explain how the system would handle the situation if a user entered "I need a registration form for a new user" in English.

[0602] In this way, the server, terminals, and users can work together to improve system performance.

[0603] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0604] Step 1:

[0605] The user provides input.

[0606] The user enters "I need a registration form for a new user" into the input field of the terminal. The input data is in text format.

[0607] Step 2:

[0608] The device sends input to the server.

[0609] The terminal sends the text data entered by the user to the server. The HTTPS protocol is used for transmission to ensure data security. The input is text data, and the output is data sent to the server.

[0610] Step 3:

[0611] The server parses the input and determines the language used.

[0612] The server uses the Google Cloud Natural Language API to analyze the received text data. From the analysis results, it determines that the input text is English. The input is text data, and the output is the language identification result.

[0613] Step 4:

[0614] The server generates the form based on the specified language.

[0615] The server uses Handlebars.js to generate an English registration form. It uses a template engine to dynamically create the form containing the information the user is looking for. The input is the language identification result and template data, and the output is the generated form.

[0616] Step 5:

[0617] The server sends the generated form to the terminal.

[0618] The server sends the generated registration form in English to the terminal, again using the HTTPS protocol to transmit data securely. The input is the generated form, and the output is the data sent to the terminal.

[0619] Step 6:

[0620] The terminal displays the form to the user.

[0621] The terminal displays the received form to the user. The user checks the displayed form and enters the necessary information. The input is the received form, and the output is what is displayed to the user.

[0622] Step 7:

[0623] The user provides feedback on the form.

[0624] The user provides feedback about the form's usability and satisfaction, for example, by typing a comment such as "This form is very user-friendly." The input is the feedback text, and the output is the input to the terminal.

[0625] Step 8:

[0626] The device sends the feedback to the server.

[0627] The terminal sends the user's feedback to the server, again using the HTTPS protocol to transmit data securely. The input is the feedback text, and the output is the data transmission to the server.

[0628] Step 9:

[0629] The server analyzes the feedback and obtains emotional information.

[0630] The server analyzes the received feedback using IBM Watson Tone Analyzer. From the analysis results, it recognizes that the user is satisfied with the form. The input is the feedback text, and the output is the sentiment analysis result.

[0631] Step 10:

[0632] The server improves system performance based on emotional information.

[0633] The server improves the form generation algorithm based on the acquired emotional information. It learns to generate better forms in similar situations from next time onwards. The input is the emotion analysis result, and the output is the improved algorithm.

[0634] (Application example 2)

[0635] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0636] Traditional online shopping sites have struggled to provide a personalized experience based on the language and emotions of users. In particular, they lack multilingual support and product recommendations that take user emotions into account, creating a need for improved user experience.

[0637] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0638] In this invention, the server includes an automatic document generation means, a multi-language support means, an automatic error check means, an emotion recognition means, and a personalized recommendation means, which makes it possible to provide an interface according to the language used by the user and to recommend products personalized based on the user's emotions.

[0639] "Automatic document generation means" is a function in which artificial intelligence understands the information the user needs and automatically generates the necessary forms.

[0640] "Multi-language support means" refers to the ability to understand the language used by the user and provide appropriate forms and interfaces, regardless of the language used by the user.

[0641] The "automatic error checking method" is a function that points out missing parts and errors in documents in real time, eliminating the need to resubmit documents.

[0642] "Emotion recognition means" is a function that analyzes the user's emotions and uses that information to improve the system's performance.

[0643] "Personalized recommendations" is a feature that recommends appropriate products and services based on the user's emotions and language.

[0644] To implement this invention, a system including a server, a user terminal, and an artificial intelligence model is required. A specific embodiment of this system is shown below.

[0645] System Configuration

[0646] 1. Server: The server includes an automatic document generation means, a multi-language support means, an automatic error checking means, an emotion recognition means, and a personalized recommendation means.

[0647] 2. User terminal: A user terminal is a device such as a smartphone, tablet, or PC that provides an interface for the user to access the system.

[0648] 3. Artificial Intelligence Models: Generative AI models are used to analyze user input and generate appropriate forms and recommendations.

[0649] Program processing

[0650] The server receives input from the user terminal and performs the following processing.

[0651] 1. Language detection and translation: The server detects the user's input language using the langdetect library and translates it to English if necessary using the TextBlob library.

[0652] 2. Sentiment analysis: The server analyzes the sentiment of the user's input text using a pipeline from the transformers library.

[0653] 3. Form generation: The server generates a form according to the user's language.

[0654] 4. Personalized recommendation: The server recommends appropriate products and services based on the user's emotions and language.

[0655] Hardware and software used

[0656] Hardware: Servers, user devices (smartphones, tablets, PCs)

[0657] Software: langdetect library, TextBlob library, transformers library

[0658] Specific examples

[0659] For example, if a user types "I really love this product!", the server translates the text, analyzes the sentiment, generates appropriate forms, and recommends related products and services based on the user's sentiment.

[0660] Prompt Sentence Examples

[0661] If a user types "I love this product!", the system should translate the text, analyze the sentiment, and generate the appropriate form.

[0662] In this way, a personalized experience can be provided based on the user's language and emotions.

[0663] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0664] Step 1:

[0665] A user accesses the system using a terminal and enters text into an input form, for example, "I really like this product!" The input data is sent to the server.

[0666] Step 2:

[0667] The server detects the language of the received text data using the langdetect library. The input is the user's text and the output is the detected language code (e.g., 'ja').

[0668] Step 3:

[0669] The server translates the text to English using the TextBlob library if the detected language is not English. The input is the user's text and the detected language code, and the output is the translated English text.

[0670] Step 4:

[0671] The server performs sentiment analysis on the translated text using a pipeline of the transformers library. The input is the translated English text, and the output is the result of the sentiment analysis (e.g., 'POSITIVE').

[0672] Step 5:

[0673] The server generates a form according to the user's language. For example, if the user's language is Japanese, it generates a Japanese form. The input is the detected language code, and the output is the form in the corresponding language.

[0674] Step 6:

[0675] The server recommends personalized products and services based on the results of sentiment analysis and the user's language. The input is the result of sentiment analysis and the detected language code, and the output is a list of recommended products and services.

[0676] Step 7:

[0677] The server sends the generated form and a list of recommended products and services to the user's terminal, where the user can review the information and select the next action.

[0678] Example 3

[0679] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0680] Conventional document creation systems required users to manually input necessary information and check for errors and omissions, which was time-consuming and laborious. Furthermore, there was also the issue of insufficient multilingual support, making it difficult to respond when users became confused. Furthermore, support that took into account the user's emotional state was not provided, which could result in a poor user experience.

[0681] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0682] In this invention, the server includes an automatic document generation means, a multilingual support means, an automatic error checking means, an emotional state analysis means, and an emotional state-based support adjustment means. This eliminates the need for the user to input necessary information and enables missing parts and errors in the document to be identified in real time. Furthermore, by providing multilingual support according to the user's emotional state, the user can receive appropriate support even when confused, improving the overall user experience.

[0683] "Automatic document generation means" is a function in which artificial intelligence understands the information the user needs and automatically generates the necessary forms.

[0684] "Multilingual support means" refers to a function that supports users in multiple languages, and can provide support in the user's native language.

[0685] "Automatic error checking means" is a function that detects missing parts and errors in documents in real time and notifies the user.

[0686] The "emotional state analysis means" is a function that monitors the user's input and actions and analyzes the user's emotional state using emotion recognition technology.

[0687] The "means for adjusting support based on emotional state" is a function that adjusts the operation of the multilingual support means according to the emotional state of the user, and provides support in the user's native language.

[0688] The present invention relates to a system including an automatic document generation means, a multilingual support means, an automatic error check means, an emotional state analysis means, and an emotional state-based support adjustment means. Specific embodiments of this system will be described below.

[0689] First, the user uploads documents such as application forms to the system. The server receives the uploaded documents and stores them in a database. At this time, the server uses the Google Cloud Vision API to convert the document contents into text data using OCR (optical character recognition) technology. The converted text data is then analyzed to ensure that all required fields are filled in.

[0690] The server then uses the analysis results to detect missing or incorrect information. For example, if the address field is blank, the server will list the error as "The address field is blank." The detected errors are notified to the user via email or in-app notification. The user receives the notification, checks the identified areas, and corrects them. The corrected document is then uploaded again, and the server analyzes the resubmitted document again to verify that the errors have been corrected.

[0691] Additionally, the device monitors the user's input and behavior and analyzes their emotional state using the Microsoft Azure Emotion API. If the user is deemed confused, the information is sent to the server. Based on the received emotional state, the server uses the Google Translate API to adjust multilingual support options. For example, if the user's native language is Japanese, the support content will be translated into Japanese. The translated support content is then provided to the user, allowing them to receive support in their native language.

[0692] For example, if a user submits an application form but the address field is blank, the server uses the Google Cloud Vision API to detect the omission and notifies the user, "The address field is blank. Please fill it in." The user then fills in the address and submits the document again. Alternatively, if the user is receiving support in English but is recognized as confused, the server uses the Google Translate API to provide support in the user's native language, Japanese.

[0693] Examples of prompts include "Detect and notify users of missing parts in their submitted documents" and "Provide support in their native language if users are confused."

[0694] The above is a specific embodiment for carrying out the present invention. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0695] Step 1:

[0696] Document upload

[0697] Users upload documents such as application forms into the system.

[0698] Input: Document files uploaded by the user.

[0699] Output: Document file saved on the server.

[0700] Specific behavior: The user selects a document through the web interface and clicks the upload button.

[0701] Step 2:

[0702] Document storage

[0703] The server receives the uploaded documents and stores them in a database.

[0704] Input: Document files uploaded by the user.

[0705] Output: Document data stored in a database.

[0706] Specific operation: The server receives the document file and creates an entry to store in the database.

[0707] Step 3:

[0708] Document analysis

[0709] The server uses the Google Cloud Vision API to convert the contents of the document into text data using OCR technology.

[0710] Input: Document data stored in a database.

[0711] Output: Document contents converted into text data.

[0712] Specific operation: The server calls the Google Cloud Vision API and converts the document image data into text data.

[0713] Step 4:

[0714] Detecting errors

[0715] The server parses the converted text data to ensure that all required fields are filled in.

[0716] Input: Document contents converted to text data.

[0717] Output: A list of detected omissions and errors.

[0718] What happens: The server parses the text data and checks whether predefined required fields are filled.

[0719] Step 5:

[0720] Error Notification

[0721] The server will send email and / or in-app notifications to notify the user of any detected errors.

[0722] Input: A list of detected omissions and errors.

[0723] Output: The error message sent to the user.

[0724] Specific behavior: The server generates an error message and sends a notification to the user.

[0725] Step 6:

[0726] Corrections and resubmission

[0727] The user can correct any errors and upload the document again.

[0728] Input: User-modified document file.

[0729] Output: The modified document file saved back to the server.

[0730] Specific behavior: The user checks the error message, corrects the document, and uploads it again.

[0731] Step 7:

[0732] Emotional state analysis

[0733] The device monitors the user's input and actions and analyzes their emotional state using the Microsoft Azure Emotion API.

[0734] Input: User input and behavioral data.

[0735] Output: Parsed emotional state of the user.

[0736] Specific operation: The device monitors the user's input and actions in real time and calls APIs to analyze their emotional state.

[0737] Step 8:

[0738] Sending emotional states

[0739] The terminal transmits the user's emotional state to the server.

[0740] Input: Parsed user emotional state.

[0741] Output: Emotional state data sent to the server.

[0742] Specific operation: The terminal makes a request to send the analysis results to the server.

[0743] Step 9:

[0744] Support Adjustments

[0745] The server adjusts its multilingual support measures using the Google Translate API based on the received emotional state.

[0746] Input: User emotional state data.

[0747] Output: Adjusted multilingual support content.

[0748] Specific operation: The server translates the support content based on the emotional state and provides it in the appropriate language.

[0749] Step 10:

[0750] Providing support

[0751] The server provides the translated support content to the user.

[0752] Input: Adjusted multilingual support content.

[0753] Output: The support provided to the user.

[0754] Specific operation: The server sends the translated support content to the user so that the user can receive appropriate support.

[0755] (Application example 3)

[0756] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0757] In conventional electronic payment systems, it is often difficult for users to detect input errors or missing parts, resulting in the time-consuming task of resubmitting the data. Furthermore, the lack of support tailored to the user's emotional state creates a problem of complicated procedures and increased stress, especially for users who are in a hurry or confused.

[0758] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes an automatic generation means, a multi-language support means, an automatic error check means, an emotion engine means, and a means for providing support according to the user's emotional state. This makes it possible to point out input errors and omissions in real time when the user makes an electronic payment, and to provide an appropriate support message according to the user's emotional state.

[0759] "Automatic generation means" is a function in which artificial intelligence understands the information the user needs and automatically generates the necessary form.

[0760] "Multi-language support means" refers to a function that supports users in multiple languages.

[0761] The "automatic error checking method" is a function that points out missing parts and errors in documents in real time, eliminating the need to resubmit documents.

[0762] The "emotion engine means" is a function that analyzes the user's emotional state.

[0763] The "means for providing support according to the user's emotional state" is a function that provides an appropriate support message according to the user's emotional state.

[0764] The system for implementing this invention comprises a server and a user terminal. The server includes an automatic generation means, a multi-language support means, an automatic error check means, an emotion engine means, and a means for providing support according to the user's emotional state.

[0765] A user terminal is a device such as a smartphone, tablet, or PC that a user uses to make electronic payments. The information entered by the user into the terminal is sent to the server.

[0766] The server first uses an automatic generation method to understand the information the user needs and automatically generate the necessary form using artificial intelligence. Next, an automatic error checking method points out missing parts and errors in the document in real time and prompts the user to make corrections.

[0767] Furthermore, an emotion engine means analyzes the user's emotional state. The emotion engine uses a natural language processing library such as TextBlob to detect emotions from the user's input text. Once the emotional state is detected, a support provision means according to the user's emotional state provides an appropriate support message. For example, if the user is anxious, the system will explain in simpler terms to help the user relax.

[0768] For example, if a user enters "12345abc," the server determines that the input is correct and prompts the user to proceed to the next step. If there is an input error, the emotion engine analyzes the user's emotional state and provides an appropriate support message.

[0769] Example prompts to input to a generative AI model:

[0770] Create a program that can point out input errors and omissions in real time when users are making electronic payments, and use an emotion engine to provide support based on the user's emotional state. If the user is in a hurry, the system can explain things in simpler terms to help them relax.

[0771] This allows users to make electronic payments smoothly, makes it easier to correct input errors and omissions, and provides support tailored to the user's emotional state, reducing stress and providing a more pleasant user experience.

[0772] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0773] Step 1:

[0774] The user enters electronic payment information into the terminal. The entered information is sent from the user's terminal to the server. The entered data includes the payment amount, payee, and the user's personal information.

[0775] Step 2:

[0776] The server uses an automatic generation method to understand the information the user needs using artificial intelligence and automatically generate the necessary form. The server analyzes the input data and processes it to generate an appropriate form. The generated form is then displayed to the user.

[0777] Step 3:

[0778] The user checks the generated form and enters the required information. The entered information is sent back to the server, which receives the input data and proceeds to the next processing step.

[0779] Step 4:

[0780] The server uses automated error checking to identify missing or incorrect documents in real time. It analyzes the input data and performs data calculations to detect missing or incorrect documents. If an error is detected, a message is displayed prompting the user to correct it.

[0781] Step 5:

[0782] The user makes corrections according to the error message. The corrected information is sent to the server again. The server receives the corrected data and checks for errors again.

[0783] Step 6:

[0784] The server analyzes the user's emotional state using an emotion engine means. It analyzes the user's input text and performs data calculations to detect emotions. The emotion engine uses a natural language processing library such as TextBlob.

[0785] Step 7:

[0786] The server uses a support provision method that corresponds to the user's emotional state to provide an appropriate support message. It processes data to select the message to display to the user based on the user's emotional state. For example, if the user is anxious, the system will explain in simpler terms to help the user relax.

[0787] Step 8:

[0788] The user follows the support messages to make final confirmations and corrections. If all information is correct, the payment is completed. The server receives the final data and processes the payment. The user is notified that the payment has been completed.

[0789] The above processing steps allow users to smoothly complete electronic payments, make it easy to correct input errors or omissions, and provide support tailored to the user's emotional state, reducing stress and providing a more comfortable user experience.

[0790] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0791] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0792] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0793] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0794] [Second embodiment]

[0795] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0796] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0797] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0798] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0799] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0800] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0801] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0802] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0803] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0804] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0805] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0806] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0807] "Example 1"

[0808] One aspect of the present invention is a system that includes a means for automatically generating documents required by city hall, a means for multi-language support, and a means for automatic error checking. Specifically, AI understands the information required by the user and automatically generates the required form. For example, when creating an application form required by city hall, the user inputs the required information (e.g., name, address, application details, etc.), and the AI ​​understands the information and automatically generates the appropriate form.

[0809] "Example 2"

[0810] Additionally, aspects of the present invention provide multi-language support. Specifically, regardless of the language used by the user, the system will understand that language and generate the appropriate form. For example, if the user uses English, the system will understand the information in English and generate an English form.

[0811] "Example 3"

[0812] Furthermore, aspects of the present invention provide an automated error checking mechanism. Specifically, the system identifies missing or incorrect documents in real time, eliminating the need for resubmission. For example, if a user has omitted a portion of an application form, the system will point out the missing portion and prompt the user to correct it.

[0813] The processing flow of each embodiment will be described below.

[0814] "Example 1"

[0815] Step 1: The user enters the required information into the system (e.g., name, address, application details, etc.).

[0816] Step 2: AI understands the information provided by the user and automatically generates the appropriate form.

[0817] Step 3: The generated form is presented to the user for correction and confirmation if necessary.

[0818] "Example 2"

[0819] Step 1: Enter your preferred language into the system.

[0820] Step 2: The system understands the user's language and generates the appropriate form for that language.

[0821] Step 3: The generated form is presented to the user for correction and confirmation if necessary.

[0822] "Example 3"

[0823] Step 1: The user submits the document to the system.

[0824] Step 2: The system checks the submitted documents for missing parts and errors in real time.

[0825] Step 3: If an error is detected, the system notifies the user and prompts them to correct it.

[0826] Example 1

[0827] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0828] Creating documents required by city hall is time-consuming and error-prone for users. Furthermore, the complexity increases when multilingual support is required. This often leads to users wasting time and effort by having to resubmit documents. An efficient system to solve these problems is needed.

[0829] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0830] In this invention, the server includes a means for a user to input necessary information, a means for analyzing the input information, a means for automatically generating documents based on the analysis results, a means for providing the generated documents in multiple languages, and a means for performing error checks on the generated documents. This allows users to easily create the necessary documents and provides them in multiple languages, making them usable across language barriers. Furthermore, error checks can eliminate the need for resubmission.

[0831] "User" refers to an individual or organization that uses the system to prepare the necessary documents at City Hall.

[0832] "Means for inputting information" refers to the interface that allows users to input necessary information such as name, address, and application details into the system.

[0833] "Means for analyzing information" refers to technologies, such as generative AI models, used to analyze input information and generate appropriate documents.

[0834] "Means for automatically generating documents" refers to a function that automatically creates the necessary documents based on the analyzed information.

[0835] "Means for providing in multiple languages" refers to a technology for translating the generated document into multiple languages ​​and providing it to the user.

[0836] "Means for error checking" refers to the function of checking the accuracy and appropriateness of the input content of generated documents and detecting errors.

[0837] "Generative AI model" refers to the artificial intelligence technology used to analyze user-entered information and generate appropriate documents.

[0838] "Means for verifying the existence of an address" refers to technology for verifying whether the entered address actually exists.

[0839] "Error check rules" refer to predefined criteria and conditions for verifying the appropriateness of application content.

[0840] This invention is a system for efficiently creating documents required by city hall. The system allows users to input the necessary information, analyzes that information, automatically generates appropriate documents, provides them in multiple languages, and also has the ability to check for errors.

[0841] Hardware and software used

[0842] Hardware

[0843] Server: A central processing unit for analyzing information, generating documents, translating into multiple languages, and checking for errors.

[0844] Terminal: The device (e.g., computer, smartphone) where a user enters information and reviews the resulting documents.

[0845] software

[0846] Generative AI model: An artificial intelligence technique (e.g., GPT-4) used to analyze user-entered information and generate appropriate documents.

[0847] Translation API: A service for translating generated documents into multiple languages ​​(e.g., Google Translate API).

[0848] Map API: A service that checks the existence of an entered address (e.g., Google Maps API).

[0849] Program processing

[0850] Enter user information

[0851] The user accesses the system's web interface and enters the necessary information, such as name, address, application details, etc. For example, the user enters "Taro Tanaka, Shinjuku Ward, Tokyo, application for copy of resident registration card."

[0852] Sending information

[0853] The device sends the information entered by the user to the server in JSON format. The data sent is in the following format:

[0854] json

[0855] {

[0856] "name": "Taro Tanaka",

[0857] "address": "Shinjuku-ku, Tokyo",

[0858] "application_content": "Application for a copy of residence certificate"

[0859] }

[0860] Analysis of information

[0861] The server inputs the received JSON data into a generative AI model (e.g., GPT-4), which analyzes the user's input and selects an appropriate application form template.

[0862] Generate a form

[0863] The server automatically generates an application form based on the analysis results obtained from the generative AI model. For example, it generates a form containing the necessary fields for "application for a copy of resident registration."

[0864] Multilingual support

[0865] The server translates the generated Japanese form into English and Spanish using the Google Translate API. The translated form is then provided in multiple languages, as follows:

[0866] Japanese: Application for a copy of resident registration

[0867] English: Application for a Copy of Resident Certificate

[0868] Spanish: Solicitud de Copia del Certificado de Residencia

[0869] Error Checking

[0870] The server uses the Google Maps API to verify the existence of the entered address and checks the validity of the application based on predefined rules, for example, generating an error message if the address does not exist or if the application is invalid.

[0871] Form submission

[0872] The server sends the form after error checking to the terminal. The user can review the form provided through the terminal and make corrections as necessary. For example, if the user corrects their address, the form will be checked for errors again.

[0873] Specific examples

[0874] Example 1: When a user creates an application form in Japanese

[0875] 1. The user accesses the system and enters their name, address, and application details in Japanese.

[0876] 2. The server receives the input information and analyzes it using a generative AI model (e.g., GPT-4).

[0877] 3. The server automatically generates a Japanese application form based on the analysis results.

[0878] 4. The server also translates the generated form into English using the Google Translate API.

[0879] 5. The server uses the Google Maps API to verify the existence of the address and perform other error checking.

[0880] 6. The server provides the completed error-checked form to the user.

[0881] Example 2: Example of a prompt statement

[0882] "A user enters their name, address, and application details to fill out an application form at city hall. Based on this information, please automatically generate the appropriate form and provide it in multiple languages. Please also check the input for errors."

[0883] In this way, a system is realized that allows users to easily create the documents required at city hall.

[0884] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0885] Step 1:

[0886] The user accesses the system's web interface and enters the necessary information, such as name, address, and application details. The entered information is sent from the terminal to the server. The input data is text information, such as name, address, and application details.

[0887] Step 2:

[0888] The device sends the information entered by the user to the server in JSON format. The data sent is in the following format:

[0889] json

[0890] {

[0891] "name": "Taro Tanaka",

[0892] "address": "Shinjuku-ku, Tokyo",

[0893] "application_content": "Application for a copy of residence certificate"

[0894] }

[0895] The server receives this JSON data.

[0896] Step 3:

[0897] The server inputs the received JSON data into a generative AI model (e.g., GPT-4). The generative AI model analyzes the user's input and selects an appropriate application form template. As a result of the analysis, an application form template containing the required fields is generated.

[0898] Step 4:

[0899] The server automatically generates an application form based on the analysis results obtained from the generative AI model. For example, a form containing the necessary fields for "application for a copy of resident registration" is generated. The generated form is customized based on the information entered by the user.

[0900] Step 5:

[0901] The server translates the generated Japanese form using a translation API (e.g., Google Translate API) to provide it in multiple languages. The translated form is provided in multiple languages, such as English and Spanish. For example, the Japanese "Application for a Copy of Resident Certificate" is translated into English "Application for a Copy of Resident Certificate."

[0902] Step 6:

[0903] The server performs automatic error checking on the generated form. It uses the Google Maps API to check whether the entered address exists. It also checks whether the application details are valid based on predefined rules. For example, it generates an error message if the address does not exist or if the application details are invalid.

[0904] Step 7:

[0905] The server sends the form after error checking to the terminal. The user can review the form provided through the terminal and make corrections as necessary. For example, if the user corrects their address, the form will be checked for errors again.

[0906] (Application example 1)

[0907] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0908] Autonomous vehicles require passengers to quickly and accurately prepare the necessary documents when they arrive at their destination. However, current systems require passengers to prepare the documents manually, which can lead to language barriers and errors. This can reduce passenger convenience and delay procedures at the destination. Therefore, a system is needed that automatically generates the necessary documents before passengers arrive at their destination and checks for errors in real time.

[0909] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0910] In this invention, the server includes means for automatically generating documents required by city hall, multi-language support means, automatic error checking means, means for automatically generating documents required by passengers in the infotainment system of the autonomous vehicle before they arrive at their destination, means for passengers to input required information using a smart device, and means for AI to generate appropriate documents based on the input information, thereby enabling required documents to be prepared quickly and accurately before passengers arrive at their destination.

[0911] "Means for automatically generating documents required by city hall" is a function that automatically generates various documents required by city hall based on information entered by the user.

[0912] "Multi-language support means" refers to a function that supports multiple languages ​​and translates information entered by the user into the appropriate language.

[0913] The "automatic error checking means" is a function that detects missing parts or errors in the generated document in real time and notifies the user.

[0914] An "autonomous vehicle infotainment system" is a system installed in an autonomous vehicle that provides information and entertainment to passengers.

[0915] The "means for automatically generating necessary documents before a passenger arrives at a destination" is a function for automatically generating necessary documents before a passenger arrives at a destination.

[0916] "Means for passengers to input necessary information using smart devices" refers to a function that allows passengers to input necessary information using devices such as smartphones and tablets.

[0917] "Means for AI to generate appropriate documents based on input information" refers to a function in which artificial intelligence analyzes the information input by passengers and generates appropriate documents based on that information.

[0918] A system for implementing this invention is configured as follows: First, a server includes means for automatically generating documents required by city hall, means for multi-language support, means for automatic error checking, means for automatically generating documents required by passengers in an infotainment system of an autonomous vehicle before they arrive at their destination, means for passengers to input required information using a smart device, and means for AI to generate appropriate documents based on the input information.

[0919] Hardware and Software Configuration

[0920] Hardware: Autonomous vehicle infotainment systems, smartphones, tablets, touchscreens

[0921] Software: Python, Google Translate API, Langdetect library, generative AI model

[0922] Data processing and calculation

[0923] 1. Language detection: The server detects the language of the text entered by the user using the smart device using the Langdetect library.

[0924] 2. Translation: If necessary, translate the text into the desired language using the Google Translate API.

[0925] 3. Form generation: The server automatically generates the required document form based on the information entered by the user. It uses a generative AI model to analyze the input information and generate the appropriate document.

[0926] 4. Error checking: The server detects any missing parts or errors in the generated document in real time and notifies the user.

[0927] Specific examples

[0928] For example, to generate immigration documents required for a passenger visiting Japan for tourism purposes, the following prompt statement could be used:

[0929] Example prompt sentence:

[0930] Enter your user information:

[0931] Name: Yamada Taro

[0932] Address: Shinjuku Ward, Tokyo

[0933] Purpose: Sightseeing

[0934] By inputting this prompt into a generative AI model, the necessary documents are automatically generated. The server generates the appropriate documents based on the information entered by the user and performs error checking. This enables passengers to quickly and accurately prepare the necessary documents before arriving at their destination.

[0935] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0936] Step 1:

[0937] The user enters the required information using a smart device.

[0938] Input: A user uses a smartphone or tablet to enter information such as name, address, and purpose.

[0939] Data processing: The entered information is sent to the server.

[0940] Output: The user's input information is saved on the server.

[0941] Step 2:

[0942] The server detects the language of the input information.

[0943] Input: Text information entered by the user.

[0944] Data Computing: Detect the language of the input text using the Langdetect library.

[0945] Output: Detected language information.

[0946] Step 3:

[0947] The server translates the input information as needed.

[0948] Input: User input and detected language information.

[0949] Data processing: Use Google Translate API to translate input information into the desired language.

[0950] Output: The translated text information.

[0951] Step 4:

[0952] The server generates the required document form based on the input information.

[0953] Input: User input information (including translated information).

[0954] Data Computing: Using generative AI models to analyze input information and automatically generate appropriate document forms.

[0955] Output: The form of the generated document.

[0956] Step 5:

[0957] The server checks the generated document for errors.

[0958] Input: The form of the generated document.

[0959] Data calculation: Detect missing parts and errors in documents in real time.

[0960] Output: The result of the error check (and an error message if there is an error).

[0961] Step 6:

[0962] The server notifies the user of the results of the error check.

[0963] Input: The result of the error check.

[0964] Data processing: Generate an error message and notify the user.

[0965] Output: The error message that is displayed to the user.

[0966] Step 7:

[0967] The user corrects the error and enters the information again.

[0968] Input: The user corrects the information based on the error message and re-enters it.

[0969] Data processing: The corrected information is sent to the server again.

[0970] Output: The corrected information stored on the server.

[0971] Step 8:

[0972] The server regenerates the document based on the corrected information and checks for errors.

[0973] Input: Corrected information.

[0974] Data calculation: Regenerate documents using the AI ​​model and check for errors.

[0975] Output: A final error-free document form.

[0976] Step 9:

[0977] The server provides the final document to the user.

[0978] Input: Final document form without errors.

[0979] Data Processing: Formatting the final document for delivery to the user.

[0980] Output: The final document provided to the user.

[0981] Example 2

[0982] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0983] In the previous system, users had to manually generate forms in the language they used, making it difficult to support multiple languages. Furthermore, the system lacked the functionality to point out missing or errors in the data entered by users in real time, which resulted in the hassle of having to resubmit the form.

[0984] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for detecting the language used by the user, means for generating an appropriate form based on the detected language, means for transmitting the generated form to the user's terminal, means for receiving and processing data entered by the user, and means for transmitting the processing result to the user's terminal. This makes it easy to support multiple languages ​​and makes it possible to point out missing parts and errors in data entered by the user in real time.

[0985] "User" refers to any individual or entity that uses the System.

[0986] "Language" refers to the natural language used by the user, including English, Japanese, Spanish, and the like.

[0987] "Means for detecting" refers to technical means for identifying the language used by a user, including natural language processing techniques.

[0988] "Form" means an electronic form for a user to enter required information.

[0989] "Generating means" refers to the technical means for automatically generating the appropriate form based on the identified language.

[0990] "Means for sending" refers to the technical means for sending the generated form and processing results to the user's terminal.

[0991] "Terminal" refers to an electronic device used by a user to access the system, including a personal computer, smartphone, tablet, etc.

[0992] "Means for receiving" refers to the technical means by which the server receives the data entered by the user.

[0993] "Processing means" refers to the technical means for analysing received data and producing the required result.

[0994] A "missing portion" refers to a portion where information that should be entered by the user is missing.

[0995] "Error" refers to an error in the data entered by the user.

[0996] "Real-time" refers to processing occurring immediately as the user enters data.

[0997] "Resubmission" refers to the act of a user correcting errors or omissions and then sending the data again.

[0998] This invention is a system that automatically detects the language used by the user, generates an appropriate form, and provides it to the user. The system consists of three main elements: a server, a terminal, and a user.

[0999] The server uses natural language processing technology to detect the language used by the user, specifically using services such as Google Cloud Natural Language API and Microsoft Azure Text Analytics API. The server analyzes the user's input data and identifies the language used.

[1000] The server then generates the appropriate form based on the identified language. The server retrieves a template from the database that corresponds to the user's language and generates the form based on that template. For example, if the user speaks English, the server creates the form using the English template.

[1001] The generated form is sent from the server to the user's device. The server transmits data using the HTTP protocol, specifically through a RESTful API. The device parses the received form data and displays it in a user interface. The device renders the form using a front-end framework such as React or Vue.js.

[1002] The user enters the necessary information into the displayed form and presses the submit button. The device then generates an HTTP request again to send the data entered by the user to the server. The server processes the received data and generates the necessary results, such as saving it in a database or linking it to other services.

[1003] The processing results are sent from the server to the terminal, which then displays them to the user, allowing the user to check whether their input has been processed correctly.

[1004] As a concrete example, consider the case where a user inputs "I need a registration form" in English. The terminal sends this input data to the server, which analyzes the input data and determines that the user is using English. The server generates a registration form using an English template and sends the generated English registration form to the terminal. The terminal displays the received English registration form to the user, who enters the required information and submits it. The server processes the received data, generates a result, and sends it to the terminal, which then displays the result to the user.

[1005] An example of a prompt is as follows:

[1006] "Parse data entered by the user in English and generate an English form."

[1007] "Please parse the data entered by the user in Japanese and generate a form in Japanese."

[1008] In this way, the system can generate and present the appropriate form to the user regardless of the language the user uses.

[1009] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1010] Step 1:

[1011] The user selects or types a language.

[1012] Input: The language used by the user (e.g. English, Japanese)

[1013] How it works: The user selects the language they want to use on the system interface or enters it directly.

[1014] Output: Selected or entered language information

[1015] Step 2:

[1016] The terminal sends the user's input to the server.

[1017] Input: Language information selected or entered by the user

[1018] Operation: The terminal sends the language information selected or entered by the user to the server by generating an HTTP POST request.

[1019] Output: Language information sent to the server

[1020] Step 3:

[1021] The server detects the user's language.

[1022] Input: Language information sent to the server

[1023] How it works: The server analyzes the received data and determines the language used by the user, specifically using natural language processing techniques.

[1024] Output: Identified language information

[1025] Step 4:

[1026] The server generates the appropriate form.

[1027] Input: Identified language information

[1028] How it works: The server generates the appropriate form based on the language identified, by retrieving the corresponding template from the database and creating the form based on that template.

[1029] Output: The generated form data

[1030] Step 5:

[1031] The server sends the generated form to the terminal.

[1032] Input: Generated form data

[1033] How it works: The server sends the generated form data to the terminal, specifically via a RESTful API using the HTTP protocol.

[1034] Output: Form data sent to the terminal

[1035] Step 6:

[1036] The terminal displays the form to the user.

[1037] Input: Form data sent to the terminal

[1038] What it does: The terminal parses the received form data and displays it in a user interface, specifically by rendering the form using a front-end framework such as React or Vue.js.

[1039] Output: The form displayed to the user

[1040] Step 7:

[1041] The user fills in the required information in the form and submits it.

[1042] Input: Information entered by the user (e.g., name, email address)

[1043] How it works: The user enters the required information into the displayed form and presses the submit button.

[1044] Output: The information entered

[1045] Step 8:

[1046] The terminal sends the input data to the server.

[1047] Input: Information entered

[1048] Operation: The terminal generates an HTTP POST request to send the data entered by the user to the server.

[1049] Output: The input data sent to the server

[1050] Step 9:

[1051] The server processes the input data and produces a result.

[1052] Input: Input data sent to the server

[1053] Operation: The server analyzes the received data and generates the necessary results, such as storing them in a database or connecting to other services.

[1054] Output: Generated result data

[1055] Step 10:

[1056] The server sends the results to the terminal.

[1057] Input: Generated result data

[1058] Operation: The server sends the generated result data to the terminal. Specifically, it sends the data in JSON format again via the RESTful API.

[1059] Output: Result data sent to the terminal

[1060] Step 11:

[1061] The terminal displays the results to the user.

[1062] Input: Result data sent to the terminal

[1063] How it works: The device parses the result data received from the server and displays it in the user interface. Specifically, it uses React to render the results.

[1064] Output: The result displayed to the user

[1065] (Application example 2)

[1066] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1067] With the previous system, it was difficult to automatically generate the appropriate form according to the user's language, which led to a poor user experience, especially in environments where multilingual support was required. Furthermore, the system lacked the functionality to point out missing or incorrect documents in real time, which often required users to resubmit documents.

[1068] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an automatic document generation means, a multi-language support means, an automatic error check means, a means for detecting the user's input language, and a means for generating an appropriate form based on the detected language. This makes it possible to automatically generate an appropriate form according to the language used by the user, and by pointing out missing parts and errors in the document in real time, it becomes possible to eliminate the need for resubmission.

[1069] "Automatic document generation means" is a function that automatically creates appropriate documents and forms based on the information required by the user.

[1070] "Multi-language support means" refers to a function that supports multiple languages ​​used by users and provides appropriate information in each language.

[1071] "Automatic error checking means" is a function that detects missing parts and errors in documents in real time and points them out to the user.

[1072] A "means for detecting the user's input language" is a function that automatically identifies the language of text entered by the user.

[1073] The "means for generating an appropriate form based on the detected language" is a function that automatically generates an appropriate form in a language that the user can easily understand, depending on the detected language.

[1074] A system for implementing the present invention includes means for automatically generating documents, means for multi-language support, means for automatic error checking, means for detecting a user's input language, and means for generating an appropriate form based on the detected language.

[1075] The server uses a language detection library (e.g., langdetect) to automatically identify the language of the text entered by the user. If the text entered by the user is Japanese, it generates a Japanese form, and if it is English, it generates an English form. This process involves using Google's translation API (googletrans library) to translate the text if necessary.

[1076] Specifically, if a user types "search for products" on a smartphone, the server receives this input and uses a language detection library to identify that it is in Japanese. It then generates a Japanese form and provides it to the user, allowing the user to search for products in their own language and proceed with the purchase process.

[1077] The server also uses automated error checking to detect missing or incorrect parts of the generated form in real time and notify the user, saving the user the trouble of having to resubmit the form.

[1078] The hardware used is a smartphone, and the software is Python, the langdetect library, and the googletrans library.

[1079] For example, if a user types "Search for products", a Japanese form will be generated. An example of this prompt is:

[1080] If a user types "Search for products", generate a form in Japanese.

[1081] In this way, it is possible to automatically generate the appropriate form according to the language used by the user, and by pointing out missing parts or errors in the document in real time, it is possible to eliminate the need to resubmit the form.

[1082] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1083] Step 1:

[1084] A user uses a smartphone to input text, for example, "Search for a product." This input text is sent to the system.

[1085] Step 2:

[1086] The server analyzes the received input text using a language detection library (langdetect) to identify the language of the input text. The input is the user's text, and the output is the identified language (Japanese in this case).

[1087] Step 3:

[1088] The server generates an appropriate form based on the identified language, where templates for form generation are available and a template is selected depending on the language, the input is the identified language, and the output is the generated form.

[1089] Step 4:

[1090] The server sends the generated form to the user's smartphone, where the user can view the form displayed in their own language. The input is the generated form, and the output is the form displayed on the user's smartphone.

[1091] Step 5:

[1092] The user fills in the form and presses the submit button. The entered data is sent to the server. The input is the data the user entered into the form, and the output is the data sent to the server.

[1093] Step 6:

[1094] The server uses automatic error checking to detect missing or erroneous data in real time. The input is the data sent by the user, and the output is the detected error information.

[1095] Step 7:

[1096] The server notifies the user of the detected error information. The user receives instructions for correcting the error, and can correct the form again and submit it. The input is the detected error information, and the output is the error information notified to the user.

[1097] Step 8:

[1098] The user corrects the errors and submits the form again. The server receives the data again and checks for errors. If there are no errors, the data is processed successfully. The input is the corrected data, and the output is the successfully processed data.

[1099] In this way, an appropriate form is automatically generated according to the language used by the user, and error checking is performed in real time.

[1100] Example 3

[1101] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1102] Conventional document submission systems required users to manually check and correct missing or incorrect documents, resulting in time-consuming resubmissions. Furthermore, they lacked multilingual support, making them difficult for users who speak different languages. Furthermore, they lacked the technology to accurately analyze document content, resulting in low error detection accuracy.

[1103] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1104] In this invention, the server includes an automatic document generation means, a multilingual support means, an automatic error check means, an optical character recognition means, an analysis means using a generative AI model, and a real-time notification means. This allows missing parts and errors in documents submitted by users to be detected in real time and prompt corrections to be made. Multilingual support also makes it easy for users who speak different languages ​​to use the system. Furthermore, analysis using a generative AI model allows for highly accurate analysis of the document contents, improving the accuracy of error detection.

[1105] "Automatic document generation means" is a function that automatically generates the necessary forms based on the information required by the user.

[1106] "Multilingual support means" refers to a function that provides system functions and interfaces in multiple languages ​​to users who speak different languages.

[1107] "Automatic error checking means" is a function that detects missing parts or errors in submitted documents in real time and notifies the user.

[1108] "Optical character recognition means" is a technology for converting uploaded documents into text data.

[1109] "Analysis means using a generative AI model" is a function that uses a generative AI model to analyze text data and understand the contents of a document.

[1110] "Real-time notification means" is a function that immediately notifies the user of detected missing parts or errors.

[1111] This invention is a system that detects missing parts and errors in documents submitted by users in real time and prompts them to correct them quickly. The system includes an automatic document generation means, a multilingual support means, an automatic error check means, an optical character recognition means, an analysis means using a generative AI model, and a real-time notification means.

[1112] First, the user accesses the system interface using a terminal and uploads documents such as application forms. The documents to be uploaded are in PDF or image format. The server receives the documents uploaded by the user and temporarily stores them on the server.

[1113] The server then uses optical character recognition (e.g., Tesseract OCR) to convert the uploaded document into text data, which converts images and PDF documents into parseable text data.

[1114] The server uses a generative AI model (e.g., OpenAI GPT-4) to analyze the converted text data. The goal of the analysis is to understand the content of the document and identify gaps and errors. Examples of prompts to input to the generative AI model include:

[1115] Analyze the application submitted by the user to detect missing parts and errors. Analyze the following text data:

[1116] [Text data]

[1117] The server uses the results of the generative AI model's analysis to detect missing parts and errors in the document, such as missing required fields or incorrect formatting.

[1118] Any missing or errors detected are notified to the user using real-time notification methods. Notifications are displayed in real time on the system interface, and can also be sent by email or other means if necessary.

[1119] For example, suppose a user uploads a mortgage application. The application is missing the annual income field. When the user uploads the application, the server receives the document and converts it into text data using Tesseract OCR. Next, it analyzes the text data using a generative AI model (e.g., OpenAI GPT-4) and detects that the annual income field is missing. Based on this information, the server notifies the user, "The annual income field is missing. Please correct it." The user receives this notification, fills in the annual income field, and uploads the application again.

[1120] In this way, users can quickly correct missing parts and errors in documents, eliminating the need to resubmit them. Multilingual support also makes it easy for users who speak different languages ​​to use the system. Furthermore, analysis using a generative AI model enables highly accurate analysis of document content, improving the accuracy of error detection. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[1121] Step 1:

[1122] User uploads document

[1123] Users access the system interface using a terminal and upload documents such as application forms. The input is documents in PDF format or image format, and the output is the document data sent to the server.

[1124] Step 2:

[1125] The server receives the document

[1126] The server receives the document uploaded by the user and temporarily stores it in the server. The input is the document data sent by the user, and the output is the document data stored in the server.

[1127] Step 3:

[1128] The server converts the document into text data using OCR software.

[1129] The server converts the uploaded document into text data using optical character recognition (e.g., "Tesseract OCR"). The input is the document data stored on the server, and the output is text data. Specifically, the OCR software analyzes the document image and extracts the text information.

[1130] Step 4:

[1131] The server analyzes the text data using a generative AI model

[1132] The server uses a generative AI model (such as OpenAI GPT-4) to analyze the converted text data. The input is the text data, and the output is the analysis result. Specifically, the generative AI model analyzes the text data based on the prompt and understands the content of the document.

[1133] Step 5:

[1134] The server detects missing parts and errors based on the analysis results.

[1135] The server detects missing parts and errors in documents based on the analysis results of the generative AI model. The input is the analysis results, and the output is a list of missing parts and errors. Specifically, it collates the analysis results and identifies missing required fields and formatting errors.

[1136] Step 6:

[1137] The server notifies the user of any missing parts or errors

[1138] The server notifies the user of any missing parts or errors that it detects. The input is a list of missing parts or errors, and the output is a notification message to the user. Specifically, the server displays a notification in real time on the system interface and notifies the user by email or other means if necessary.

[1139] Step 7:

[1140] The user corrects the document and resubmits it

[1141] The user receives a notification from the server and corrects any missing parts or errors that have been pointed out. After the corrections are complete, the user uploads the document again and resubmits it. The input is the notification message from the server, and the output is the corrected document data. Specifically, the user corrects the document and uploads it to the system again.

[1142] (Application example 3)

[1143] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1144] The existing system lacked the ability to automatically generate documents required by city hall or to support multiple languages. Furthermore, it lacked the functionality to point out missing or incorrect documents in real time, forcing users to go through the trouble of resubmitting them. Furthermore, there was a problem with missing or incorrect information being easily input when entering electronic payment information, which led to frequent payment errors. A system that could solve these issues was needed.

[1145] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1146] In this invention, the server includes a means for automatically generating documents required by the city hall, a multi-language support means, an automatic error checking means, and a means for pointing out missing or error parts in electronic payment information in real time and prompting the user to correct them. This makes it possible to point out missing or error parts in documents in real time, eliminating the need for resubmission. Furthermore, when inputting electronic payment information, by pointing out missing or error parts in real time and prompting the user to correct them, payment errors can be reduced.

[1147] A "city hall" is an administrative agency of a local government and a facility that provides various administrative services to citizens.

[1148] An "automatic document generation means" is a system that has the function of automatically creating the necessary documents and forms based on the information required by the user.

[1149] "Multi-language support means" means a system that supports multiple languages ​​and has the ability to provide information in the language selected by the user.

[1150] An "automatic error checking means" is a system that has the function of detecting missing parts or errors in documents or input information in real time and prompting the user to make corrections.

[1151] "Electronic Payment Information" refers to information such as credit card information, address, and name required for online payments.

[1152] A "missing portion" refers to a portion where necessary information has not been entered.

[1153] An "error" is when the information entered is incorrect or out of format.

[1154] "Real-time" refers to immediate processing and feedback as users input information.

[1155] "User" refers to any individual or entity that uses the System.

[1156] "Encouraging correction" means pointing out any errors or omissions in the information entered to the user and asking them to re-enter the correct information.

[1157] A system for implementing this invention includes a server, a user terminal, and a network. The server includes a means for automatically generating documents required by the city hall, a multi-language support means, an automatic error checking means, and a means for pointing out missing or errors in electronic payment information in real time and prompting the user to correct them.

[1158] A user terminal is a device such as a smartphone, tablet, or PC that provides an interface for users to input information. Once the user uses the terminal to input the required information, the information is sent to the server.

[1159] The server first receives the information entered by the user and then uses an automated document generation method to automatically create the necessary documents and forms, using a generative AI model to analyze the user's input and generate the appropriate documents.

[1160] Multi-language support is then used to provide information in the user's language of choice, thereby accommodating users who speak different languages.

[1161] Additionally, automated error checking measures are used to detect missing or incorrect information entered by the user in real time, such as checking that credit card numbers, expiration dates, security codes, names, addresses, etc. If an error is detected, the server provides immediate feedback to the user to prompt them to correct it.

[1162] As a concrete example, consider the case where a user leaves out part of the card number when entering credit card information. In this case, the server displays an error message saying "The credit card number is invalid" and asks the user to re-enter the correct information.

[1163] Example prompts to input to a generative AI model:

[1164] Write a program that checks the credit card information entered by the user and points out any missing or incorrect information in real time. Check the following fields: credit card number, expiration date, security code, name, and address. If there are any errors in each field, add the errors to a list and provide feedback to the user.

[1165] This system can point out missing or errors in documents in real time, eliminating the need for resubmissions. It can also point out missing or errors in electronic payment information entry in real time and prompt users to correct them, reducing payment errors.

[1166] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1167] Step 1:

[1168] The user uses the terminal to enter the required information.

[1169] Input: Information entered by the user through the device interface (e.g., credit card number, expiration date, security code, name, address).

[1170] Output: The entered information is sent from the terminal to the server.

[1171] Step 2:

[1172] The server analyzes the received information and automatically creates the necessary documents and forms using an automatic document generation means.

[1173] Input: User input sent from the device.

[1174] Data processing: Using generative AI models to analyze user input and generate appropriate documents.

[1175] Output: The generated documents or forms.

[1176] Step 3:

[1177] The server uses multi-language support to provide information in the language selected by the user.

[1178] Input: User input and language selection.

[1179] Data processing: Translate information based on the selected language and provide it to the user.

[1180] Output: Information displayed in the user's language of choice.

[1181] Step 4:

[1182] The server uses automated error checking measures to detect missing or incorrect information entered by the user in real time.

[1183] Input: User input information.

[1184] Data processing: Use regular expressions and other validation algorithms to detect missing or error information in input.

[1185] Output: A list of detected errors and omissions.

[1186] Step 5:

[1187] The server provides feedback to the user to prompt them to correct any errors or omissions it detects.

[1188] Input: A list of detected errors and omissions.

[1189] Data processing: Generate an error message and display it to the user.

[1190] Output: The error message that is displayed to the user.

[1191] Step 6:

[1192] The user corrects the information based on the error message and re-enters it.

[1193] Input: User-modified information.

[1194] Output: The corrected information is sent to the server again.

[1195] Step 7:

[1196] The server parses the information again to ensure there are no errors.

[1197] Input: Corrected information.

[1198] Data processing: Validate input information again using regular expressions or other validation algorithms.

[1199] Output: If there are no errors, processing is complete. If there are errors, go back to step 5 again.

[1200] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1201] "Example 1"

[1202] One embodiment of the present invention provides a system incorporating an emotion engine. This system recognizes a user's emotions and adjusts its operation according to the user's emotional state. Specifically, if the system recognizes that the user is feeling stressed, it adjusts the operation of the automatic generation means and automatic error checking means to reduce the user's stress. For example, the system may change the way error messages are displayed to a gentler tone or automatically generate the necessary documents more smoothly.

[1203] "Example 2"

[1204] The emotion engine also recognizes users' feelings of joy and satisfaction and uses that information to improve system performance. For example, if the system recognizes that a user is satisfied with the automated generation of a particular form, it can learn how to generate that form and improve form generation in similar situations.

[1205] "Example 3"

[1206] Furthermore, the emotion engine also adjusts the operation of the multi-language support measures according to the user's emotional state. For example, if the system recognizes that the user is confused, it will strengthen support in the user's native language. This allows the user to receive support in their own language, clear up their confusion, and smoothly proceed with completing the necessary documents.

[1207] The processing flow of each embodiment will be described below.

[1208] "Example 1"

[1209] Step 1: The system recognizes the user's emotions using an emotion engine.

[1210] Step 2: If the emotion engine recognizes the user's stress, the system adjusts the behavior of the automatic generation and error checking measures.

[1211] Step 3: Specifically, we will change the way error messages are displayed to a gentler tone and make the automatic generation of necessary documents smoother.

[1212] "Example 2"

[1213] Step 1: The emotion engine recognizes the user's joy or satisfaction.

[1214] Step 2: If the user recognizes that they are happy with the auto-generation of a particular form, the system learns how to generate that form.

[1215] Step 3: Use the learned information to improve form generation in similar situations.

[1216] "Example 3"

[1217] Step 1: The emotion engine adjusts the behavior of the multi-language support means according to the user's emotional state.

[1218] Step 2: If the system recognizes that the user is confused, it will provide more support in the user's native language.

[1219] Step 3: This allows users to receive support in their own language, clearing up any confusion and facilitating the creation of the necessary documents.

[1220] Example 1

[1221] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1222] Creating documents required by city hall is a cumbersome and time-consuming process for users. Furthermore, when multilingual support is required or when document error checking is required, the process becomes even more time-consuming. Furthermore, users may find it difficult to operate the system in stressful situations. An efficient system that can solve these problems is needed.

[1223] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes an automatic generation means, a multilingual support means, an automatic error check means, an emotion recognition means, a user information input means, an information transmission means, and a feedback provision means. This makes it possible to quickly and accurately automatically generate documents required by the user, support multiple languages, perform error checks, and further adjust the operation of the system according to the user's emotional state.

[1224] "Automatic generation means" is a function that automatically generates necessary documents and forms based on information entered by the user.

[1225] "Multilingual support means" is a function that translates generated documents and forms into multiple languages ​​and provides them in the language selected by the user.

[1226] "Automatic error checking means" is a function that automatically detects missing parts and errors in generated documents and forms and points them out in real time.

[1227] "Emotion recognition means" is a function that analyzes the user's emotional state and adjusts the system's operation according to that emotional state.

[1228] "User information input means" is a function that provides an interface for the user to input necessary information.

[1229] "Information transmission means" is a function that transmits information entered by the user to the server.

[1230] The "feedback providing means" is a function that displays information and error messages received from the server to the user and provides necessary feedback.

[1231] MODE FOR CARRYING OUT THE INVENTION

[1232] The present invention is a system for automatically generating documents required by city hall, and aims to quickly and accurately generate the necessary documents and forms based on information entered by the user. This system includes an automatic generation means, a multilingual support means, an automatic error check means, an emotion recognition means, a user information input means, an information transmission means, and a feedback provision means.

[1233] Hardware and software used

[1234] Hardware: The device (e.g., PC, smartphone, tablet) through which the user enters information and the server that processes the information.

[1235] Software: Generative AI models (e.g., OpenAI's GPT-4), translation software (e.g., Google Translate API), emotion recognition AI models, and rule-based error-checking algorithms.

[1236] Program processing

[1237] 1. Enter your user information

[1238] The user uses the terminal to enter the necessary information (e.g., name, address, application details, etc.).

[1239] The terminal temporarily stores the entered information and prepares it for the next processing step.

[1240] 2. Transmission of information

[1241] The device sends the saved user information to the server.

[1242] The server analyzes the received information and converts it into the required data format.

[1243] 3. Information Understanding and Automatic Form Generation

[1244] The server generates prompt sentences to input the received information into the generative AI model.

[1245] The server sends prompts to the generative AI model, which then automatically generates the appropriate form.

[1246] The generative AI model generates the required document form based on the prompt sentence and returns it to the server.

[1247] 4. Multilingual support

[1248] The server checks the user's language preference.

[1249] The server translates the generated form using translation software to make it multilingual.

[1250] The server sends the translated form to the terminal.

[1251] 5. Automatic Error Checking

[1252] The server validates the entered information and generated forms with automated error checking.

[1253] If an error is detected, the server generates an error message and sends it to the terminal.

[1254] 6. Emotional engine for behavior adjustment

[1255] The server analyzes the user's emotional state using an emotion recognition AI model.

[1256] If the server detects that the user is stressed, it will change the tone of the error message to be gentler.

[1257] The server will make adjustments as necessary to smooth the form generation process.

[1258] 7. Providing Feedback

[1259] The terminal displays the final form and any error messages received from the server to the user.

[1260] The user checks the displayed information and corrects or re-enters it as necessary.

[1261] Specific examples

[1262] For example, consider the case where a user applies for a copy of their resident registration card at city hall. The user enters their name "Yamada Taro," their address "Shinjuku Ward, Tokyo," and the request for a copy of their resident registration card into their device. The device then sends this information to the server. The server then sends the following prompt to the generative AI model:

[1263] Generate a form for a user to apply for a copy of their resident registration card at city hall. The user's name is "Yamada Taro," their address is "Shinjuku-ku, Tokyo," and the request is for a copy of their resident registration card.

[1264] The generative AI model generates an application form for a copy of the resident registration certificate based on this prompt and returns it to the server. The server translates the form using the Google Translate API to make it multilingual and performs error checking. If an error is detected, the emotion engine recognizes the user's stress and generates a gentle error message. Finally, the device displays the generated form and error message to the user.

[1265] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1266] Step 1: Enter your user information

[1267] The user uses the terminal to enter the necessary information (e.g., name, address, application details, etc.).

[1268] Input: Information entered by the user (name, address, application details).

[1269] The terminal temporarily stores the entered information and prepares it for the next processing step.

[1270] Output: Saved user information.

[1271] Step 2: Submit your information

[1272] The device sends the saved user information to the server.

[1273] Input: Saved user information.

[1274] The server analyzes the received information and converts it into the required data format.

[1275] Output: Parsed user information.

[1276] Step 3: Understanding the information and automatically generating the form

[1277] The server generates prompt sentences to input the received information into the generative AI model.

[1278] Input: Parsed user information.

[1279] The server sends prompts to the generative AI model, which then automatically generates the appropriate form.

[1280] The generative AI model generates the required document form based on the prompt sentence and returns it to the server.

[1281] Output: The generated form.

[1282] Step 4: Multilingual support

[1283] The server checks the user's language preference.

[1284] Input: Generated form, user language preference.

[1285] The server translates the generated form using translation software to make it multilingual.

[1286] The server sends the translated form to the terminal.

[1287] Output: The translated form.

[1288] Step 5: Automatic error checking

[1289] The server validates the entered information and generated forms with automated error checking.

[1290] Input: translated form, user information.

[1291] If an error is detected, the server generates an error message and sends it to the terminal.

[1292] Output: Error message (if necessary).

[1293] Step 6: Adjusting behavior with the emotion engine

[1294] The server analyzes the user's emotional state using an emotion recognition AI model.

[1295] Input: The user's emotional state.

[1296] If the server detects that the user is stressed, it will change the tone of the error message to be gentler.

[1297] The server will make adjustments as necessary to smooth the form generation process.

[1298] Output: Adjusted error messages, smoother form generation process.

[1299] Step 7: Provide feedback

[1300] The terminal displays the final form and any error messages received from the server to the user.

[1301] Input: Final form, error messages.

[1302] The user checks the displayed information and corrects or re-enters it as necessary.

[1303] Output: User confirmation and correction information.

[1304] (Application example 1)

[1305] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1306] Document processing at city halls is cumbersome for users, and the process becomes even more complicated when multilingual support and error checking are insufficient. Furthermore, users often feel stressed, which reduces the efficiency of the process. A system that solves these issues and reduces the burden on users is needed.

[1307] 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. In this invention, the server includes an automatic generation means for documents required by the city hall, a multi-language support means, an automatic error check means, an emotion recognition means, an interface adjustment means, and an automatic document generation means. This enables the AI ​​to understand the information required by the user and automatically generate the necessary forms. In addition, by recognizing the user's emotional state and adjusting the system's operation according to that emotional state, it is possible to reduce user stress and improve the efficiency of procedures.

[1308] A "city hall" is an administrative agency of a local government and a facility that provides various administrative services to citizens.

[1309] "Automatic document generation means" is a system that has the function of automatically creating the necessary documents based on the information entered by the user.

[1310] "Multi-language support means" refers to a system that supports multiple languages ​​and has the function of providing services in the language selected by the user.

[1311] An "automatic error checking means" is a system that has the ability to detect missing parts and errors in documents in real time and point them out to the user.

[1312] An "emotion recognition means" is a system that has the function of recognizing the user's emotional state and adjusting the system's operation based on that information.

[1313] The "interface adjustment means" is a system that has the function of adjusting the system's user interface in accordance with the user's emotional state, thereby reducing the user's stress.

[1314] "AI" is an abbreviation for artificial intelligence, a technology that allows machines to imitate human intelligence and learn and reason.

[1315] A "form" refers to a form or document that allows a user to enter required information.

[1316] "Real-time" means that data processing and information provision are immediate.

[1317] "User" refers to any individual or entity that uses the System.

[1318] The system for implementing this invention includes a means for automatically generating documents required by city hall, a multi-language support means, an automatic error check means, an emotion recognition means, and an interface adjustment means. Specific embodiments of each means will be described below.

[1319] 1. Automatic document generation method

[1320] The server automatically creates the necessary documents based on the information entered by the user. Specifically, when the user enters information such as name, address, and application details through a smartphone application, the AI ​​understands the information and automatically generates the appropriate form. The FPDF library is used to generate the documents in PDF format.

[1321] 2. Multi-language support methods

[1322] The server supports multiple languages ​​and provides services in the language selected by the user. For example, if a user selects a language such as English, Spanish, or Chinese, the system will generate documents in that language and provide them to the user. This allows many users to use the system across language barriers.

[1323] 3. Automatic Error Checking Methods

[1324] The server detects missing or incorrect information in real time and notifies the user. Specifically, it checks each field in the document based on the information entered by the user, and immediately notifies the user if there are any missing or incorrect information. This saves the user the trouble of having to resubmit the document.

[1325] 4. Emotion recognition means

[1326] The server uses the smartphone camera to recognize the user's emotional state. Specifically, it analyzes the user's facial image using the OpenCV library and determines the user's emotions using an emotion recognition model (Transformers). This allows it to determine whether the user is feeling stressed.

[1327] 5. Interface Adjustment Methods

[1328] The server adjusts the system's user interface according to the user's emotional state obtained by the emotion recognition means. For example, if it determines that the user is feeling stressed, it changes the tone of the interface to a gentler one and makes error messages more friendly. This reduces the user's stress and improves the efficiency of the procedure.

[1329] Specific examples

[1330] The user opens the smartphone app and enters the required information (name, address, application details). The smartphone camera takes a photo of the user's face and performs emotion recognition. The tone of the interface is adjusted based on the emotion recognition results. A PDF application form is automatically generated based on the entered information and provided to the user.

[1331] Prompt Sentence Examples

[1332] The user opens the smartphone app and enters the required information (name, address, application details). The smartphone camera takes a photo of the user's face and performs emotion recognition. The tone of the interface is adjusted based on the emotion recognition results. A PDF application form is automatically generated based on the entered information and provided to the user.

[1333] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1334] Step 1:

[1335] The user opens the smartphone app and enters the required information (name, address, application details). The entered information is sent from the device to the server. The server receives this information and stores it in a database. The input data is text data such as name, address, and application details.

[1336] Step 2:

[1337] The server automatically generates documents based on the received information. Specifically, it uses a generative AI model to analyze the information entered by the user and automatically generate the appropriate form. It then uses the FPDF library to generate the document in PDF format. The output is a PDF application form that reflects the user's information.

[1338] Step 3:

[1339] A user takes a facial image using a smartphone camera. The captured image is sent from the device to a server. The server receives the image and analyzes the user's emotional state using emotion recognition. Specifically, the server preprocesses the facial image using the OpenCV library and determines the emotion using an emotion recognition model (Transformers). The input is facial image data, and the output is the emotional state (e.g., stress, relaxation, etc.).

[1340] Step 4:

[1341] The server adjusts the interface based on the emotion recognition results. Specifically, if it determines that the user is feeling stressed, it changes the interface tone to a gentler one and makes error messages more friendly, thereby reducing the user's stress. The input is emotional state data, and the output is the adjusted interface settings.

[1342] Step 5:

[1343] The server provides the generated PDF application form to the user. Specifically, it sends the generated PDF to the user's device so that the user can download it. The user checks the provided application form and prints or submits it as necessary. The input is the generated PDF data, and the output is the PDF file sent to the user's device.

[1344] Example 2

[1345] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1346] Conventional automated document generation systems are sometimes unable to support the language used by users, and the systems are not improved to take into account user sentiment and feedback, resulting in a poor user experience and underperforming systems.

[1347] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1348] In this invention, the server includes an automatic document generation means, a multi-language support means, an automatic error check means, a sentiment analysis means, and a means for improving system performance based on user feedback, thereby enabling appropriate forms to be generated regardless of the language used by the user and improving system performance by taking into account the user's sentiment and feedback.

[1349] "Automatic document generation means" refers to a means that has the function of automatically generating appropriate documents and forms based on the information required by the user.

[1350] "Multi-language support means" means that the system has the ability to understand the language used by the user and generate documents and forms in the appropriate language, regardless of the language used by the user.

[1351] An "automated error checking means" is a means that has the function of checking in real time whether there are any missing parts or errors in generated documents or forms and notifying the user.

[1352] "Emotion analysis means" refers to means that has the function of analyzing user input and feedback and acquiring user emotional information.

[1353] "Means for improving system performance based on user feedback" refers to means that have the function of improving the system's algorithms and functions based on the acquired user emotional information and feedback, thereby improving performance from the next time onwards.

[1354] MODE FOR CARRYING OUT THE INVENTION

[1355] This invention is a system that automatically generates appropriate documents and forms regardless of the language used by the user, and improves the system's performance based on the user's feelings and feedback. Specific embodiments of this system are described below.

[1356] System configuration

[1357] The system consists of three main components: a server, a terminal, and a user. The server includes a means for automatic document generation, a means for multi-language support, a means for automatic error checking, a means for sentiment analysis, and a means for improving system performance based on user feedback.

[1358] Hardware and software used

[1359] The server uses the following hardware and software:

[1360] Natural language processing engine: Google Cloud Natural Language API

[1361] Template engine: Handlebars.js

[1362] Sentiment analysis engine: IBM Watson Tone Analyzer

[1363] The terminal provides an interface for receiving user input and sending it to the server. The user accesses the system through the terminal and enters the required information.

[1364] Program processing

[1365] The server analyzes the information entered by the user and identifies the language used. Specifically, it uses the Google Cloud Natural Language API to analyze the entered text data. From the analysis results, it determines the language of the entered text.

[1366] The server then generates the appropriate documents and forms based on the identified language, using Handlebars.js to dynamically create forms containing the information the user is requesting.

[1367] The generated form is sent from the server to the terminal and displayed to the user, who then checks the displayed form and enters the required information.

[1368] When a user provides feedback in the form, the device sends the feedback to the server, which uses IBM Watson Tone Analyzer to analyze the user's feedback and obtain the user's emotional information.

[1369] Based on the acquired emotional information, the server learns to improve the system's performance. Specifically, it improves the form generation algorithm and reflects this in future form generation.

[1370] Specific examples

[1371] For example, if a user enters "I need a registration form for a new user" in English, the server processes it as follows:

[1372] 1. The server uses the Google Cloud Natural Language API to determine that the input text is in English.

[1373] 2. The server generates a registration form in English using Handlebars.js.

[1374] 3. The server sends the generated English registration form to the terminal.

[1375] 4. The terminal displays the received form to the user.

[1376] 5. The user provides feedback on the form's usability, saying "This form is very user-friendly."

[1377] 6. The device sends the user's feedback to the server.

[1378] 7. The server uses IBM Watson Tone Analyzer to recognize that the user is satisfied with the form.

[1379] 8. The server improves the form generation algorithm based on the acquired emotion information.

[1380] Example prompt sentence:

[1381] Explain how the system would handle the situation if a user entered "I need a registration form for a new user" in English.

[1382] In this way, the server, terminals, and users can work together to improve system performance.

[1383] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1384] Step 1:

[1385] The user provides input.

[1386] The user enters "I need a registration form for a new user" into the input field of the terminal. The input data is in text format.

[1387] Step 2:

[1388] The device sends input to the server.

[1389] The terminal sends the text data entered by the user to the server. The HTTPS protocol is used for transmission to ensure data security. The input is text data, and the output is data sent to the server.

[1390] Step 3:

[1391] The server parses the input and determines the language used.

[1392] The server uses the Google Cloud Natural Language API to analyze the received text data. From the analysis results, it determines that the input text is English. The input is text data, and the output is the language identification result.

[1393] Step 4:

[1394] The server generates the form based on the specified language.

[1395] The server uses Handlebars.js to generate an English registration form. It uses a template engine to dynamically create the form containing the information the user is looking for. The input is the language identification result and template data, and the output is the generated form.

[1396] Step 5:

[1397] The server sends the generated form to the terminal.

[1398] The server sends the generated registration form in English to the terminal, again using the HTTPS protocol to transmit data securely. The input is the generated form, and the output is the data sent to the terminal.

[1399] Step 6:

[1400] The terminal displays the form to the user.

[1401] The terminal displays the received form to the user. The user checks the displayed form and enters the necessary information. The input is the received form, and the output is what is displayed to the user.

[1402] Step 7:

[1403] The user provides feedback on the form.

[1404] The user provides feedback about the form's usability and satisfaction, for example, by typing a comment such as "This form is very user-friendly." The input is the feedback text, and the output is the input to the terminal.

[1405] Step 8:

[1406] The device sends the feedback to the server.

[1407] The terminal sends the user's feedback to the server, again using the HTTPS protocol to transmit data securely. The input is the feedback text, and the output is the data transmission to the server.

[1408] Step 9:

[1409] The server analyzes the feedback and obtains emotional information.

[1410] The server analyzes the received feedback using IBM Watson Tone Analyzer. From the analysis results, it recognizes that the user is satisfied with the form. The input is the feedback text, and the output is the sentiment analysis result.

[1411] Step 10:

[1412] The server improves system performance based on emotional information.

[1413] The server improves the form generation algorithm based on the acquired emotion information. It learns to generate better forms in similar situations from next time onwards. The input is the emotion analysis result, and the output is the improved algorithm.

[1414] (Application example 2)

[1415] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1416] Traditional online shopping sites have struggled to provide a personalized experience based on the language and emotions of users. In particular, they lack multilingual support and product recommendations that take user emotions into account, creating a need for improved user experience.

[1417] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1418] In this invention, the server includes an automatic document generation means, a multi-language support means, an automatic error check means, an emotion recognition means, and a personalized recommendation means, which makes it possible to provide an interface according to the language used by the user and to recommend products personalized based on the user's emotions.

[1419] "Automatic document generation means" is a function in which artificial intelligence understands the information the user needs and automatically generates the necessary forms.

[1420] "Multi-language support means" refers to the ability to understand the language used by the user and provide appropriate forms and interfaces, regardless of the language used by the user.

[1421] The "automatic error checking method" is a function that points out missing parts and errors in documents in real time, eliminating the need to resubmit documents.

[1422] "Emotion recognition means" is a function that analyzes the user's emotions and uses that information to improve the system's performance.

[1423] "Personalized recommendations" is a feature that recommends appropriate products and services based on the user's emotions and language.

[1424] To implement this invention, a system including a server, a user terminal, and an artificial intelligence model is required. A specific embodiment of this system is shown below.

[1425] System Configuration

[1426] 1. Server: The server includes an automatic document generation means, a multi-language support means, an automatic error checking means, an emotion recognition means, and a personalized recommendation means.

[1427] 2. User terminal: A user terminal is a device such as a smartphone, tablet, or PC that provides an interface for the user to access the system.

[1428] 3. Artificial Intelligence Models: Generative AI models are used to analyze user input and generate appropriate forms and recommendations.

[1429] Program processing

[1430] The server receives input from the user terminal and performs the following processing.

[1431] 1. Language detection and translation: The server detects the user's input language using the langdetect library and translates it to English if necessary using the TextBlob library.

[1432] 2. Sentiment analysis: The server analyzes the sentiment of the user's input text using a pipeline from the transformers library.

[1433] 3. Form generation: The server generates a form according to the user's language.

[1434] 4. Personalized recommendation: The server recommends appropriate products and services based on the user's emotions and language.

[1435] Hardware and software used

[1436] Hardware: Servers, user devices (smartphones, tablets, PCs)

[1437] Software: langdetect library, TextBlob library, transformers library

[1438] Specific examples

[1439] For example, if a user types "I really love this product!", the server translates the text, analyzes the sentiment, generates appropriate forms, and recommends related products and services based on the user's sentiment.

[1440] Prompt Sentence Examples

[1441] If a user types "I love this product!", the system should translate the text, analyze the sentiment, and generate the appropriate form.

[1442] In this way, a personalized experience can be provided based on the user's language and emotions.

[1443] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1444] Step 1:

[1445] A user accesses the system using a terminal and enters text into an input form, for example, "I really like this product!" The input data is sent to the server.

[1446] Step 2:

[1447] The server detects the language of the received text data using the langdetect library. The input is the user's text and the output is the detected language code (e.g., 'ja').

[1448] Step 3:

[1449] The server translates the text to English using the TextBlob library if the detected language is not English. The input is the user's text and the detected language code, and the output is the translated English text.

[1450] Step 4:

[1451] The server performs sentiment analysis on the translated text using a pipeline from the transformers library. The input is the translated English text, and the output is the result of the sentiment analysis (e.g., 'POSITIVE').

[1452] Step 5:

[1453] The server generates a form according to the user's language. For example, if the user's language is Japanese, it generates a Japanese form. The input is the detected language code, and the output is the form in the corresponding language.

[1454] Step 6:

[1455] The server recommends personalized products and services based on the results of sentiment analysis and the user's language. The input is the result of sentiment analysis and the detected language code, and the output is a list of recommended products and services.

[1456] Step 7:

[1457] The server sends the generated form and a list of recommended products and services to the user's terminal, where the user can review the information and select the next action.

[1458] Example 3

[1459] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1460] Conventional document creation systems required users to manually input necessary information and check for errors and omissions, which was time-consuming and laborious. Furthermore, there was also the issue of insufficient multilingual support, making it difficult to respond when users became confused. Furthermore, support that took into account the user's emotional state was not provided, which could result in a poor user experience.

[1461] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1462] In this invention, the server includes an automatic document generation means, a multilingual support means, an automatic error checking means, an emotional state analysis means, and an emotional state-based support adjustment means. This eliminates the need for the user to input necessary information and enables missing parts and errors in the document to be identified in real time. Furthermore, by providing multilingual support according to the user's emotional state, the user can receive appropriate support even when confused, improving the overall user experience.

[1463] "Automatic document generation means" is a function in which artificial intelligence understands the information the user needs and automatically generates the necessary forms.

[1464] "Multilingual support means" refers to a function that supports users in multiple languages, and can provide support in the user's native language.

[1465] "Automatic error checking means" is a function that detects missing parts and errors in documents in real time and notifies the user.

[1466] The "emotional state analysis means" is a function that monitors the user's input and actions and analyzes the user's emotional state using emotion recognition technology.

[1467] The "means for adjusting support based on emotional state" is a function that adjusts the operation of the multilingual support means according to the emotional state of the user, and provides support in the user's native language.

[1468] The present invention relates to a system including an automatic document generation means, a multilingual support means, an automatic error check means, an emotional state analysis means, and an emotional state-based support adjustment means. Specific embodiments of this system will be described below.

[1469] First, the user uploads documents such as application forms to the system. The server receives the uploaded documents and stores them in a database. At this time, the server uses the Google Cloud Vision API to convert the document contents into text data using OCR (optical character recognition) technology. The converted text data is then analyzed to ensure that all required fields are filled in.

[1470] The server then uses the analysis results to detect missing or incorrect information. For example, if the address field is blank, the server will list the error as "The address field is blank." The detected errors are notified to the user via email or in-app notification. The user receives the notification, checks the identified areas, and corrects them. The corrected document is then uploaded again, and the server analyzes the resubmitted document again to verify that the errors have been corrected.

[1471] Additionally, the device monitors the user's input and behavior and analyzes their emotional state using the Microsoft Azure Emotion API. If the user is deemed confused, the information is sent to the server. Based on the received emotional state, the server uses the Google Translate API to adjust multilingual support options. For example, if the user's native language is Japanese, the support content will be translated into Japanese. The translated support content is then provided to the user, allowing them to receive support in their native language.

[1472] For example, if a user submits an application form but the address field is blank, the server uses the Google Cloud Vision API to detect the omission and notifies the user, "The address field is blank. Please fill it in." The user then fills in the address and submits the document again. Alternatively, if the user is receiving support in English but is recognized as confused, the server uses the Google Translate API to provide support in the user's native language, Japanese.

[1473] Examples of prompts include "Detect and notify users of missing parts in their submitted documents" and "Provide support in their native language if users are confused."

[1474] The above is a specific embodiment for carrying out the present invention. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1475] Step 1:

[1476] Document upload

[1477] Users upload documents such as application forms into the system.

[1478] Input: Document files uploaded by the user.

[1479] Output: Document file saved on the server.

[1480] Specific behavior: The user selects a document through the web interface and clicks the upload button.

[1481] Step 2:

[1482] Document storage

[1483] The server receives the uploaded documents and stores them in a database.

[1484] Input: Document files uploaded by the user.

[1485] Output: Document data stored in a database.

[1486] Specific operation: The server receives the document file and creates an entry to store in the database.

[1487] Step 3:

[1488] Document analysis

[1489] The server uses the Google Cloud Vision API to convert the contents of the document into text data using OCR technology.

[1490] Input: Document data stored in a database.

[1491] Output: Document contents converted into text data.

[1492] Specific operation: The server calls the Google Cloud Vision API and converts the document image data into text data.

[1493] Step 4:

[1494] Detecting errors

[1495] The server parses the converted text data to ensure that all required fields are filled in.

[1496] Input: Document contents converted to text data.

[1497] Output: A list of detected omissions and errors.

[1498] What happens: The server parses the text data and checks whether predefined required fields are filled.

[1499] Step 5:

[1500] Error Notification

[1501] The server will send email and / or in-app notifications to notify the user of any detected errors.

[1502] Input: A list of detected omissions and errors.

[1503] Output: The error message sent to the user.

[1504] Specific behavior: The server generates an error message and sends a notification to the user.

[1505] Step 6:

[1506] Corrections and resubmission

[1507] The user can correct any errors and upload the document again.

[1508] Input: User-modified document file.

[1509] Output: The modified document file saved back to the server.

[1510] Specific behavior: The user checks the error message, corrects the document, and uploads it again.

[1511] Step 7:

[1512] Emotional state analysis

[1513] The device monitors the user's input and actions and analyzes their emotional state using the Microsoft Azure Emotion API.

[1514] Input: User input and behavioral data.

[1515] Output: Parsed emotional state of the user.

[1516] Specific operation: The device monitors the user's input and actions in real time and calls APIs to analyze their emotional state.

[1517] Step 8:

[1518] Sending emotional states

[1519] The terminal transmits the user's emotional state to the server.

[1520] Input: Parsed user emotional state.

[1521] Output: Emotional state data sent to the server.

[1522] Specific operation: The terminal makes a request to send the analysis results to the server.

[1523] Step 9:

[1524] Support Adjustments

[1525] The server adjusts its multilingual support measures using the Google Translate API based on the received emotional state.

[1526] Input: User emotional state data.

[1527] Output: Adjusted multilingual support content.

[1528] Specific operation: The server translates the support content based on the emotional state and provides it in the appropriate language.

[1529] Step 10:

[1530] Providing support

[1531] The server provides the translated support content to the user.

[1532] Input: Adjusted multilingual support content.

[1533] Output: The support provided to the user.

[1534] Specific operation: The server sends the translated support content to the user so that the user can receive appropriate support.

[1535] (Application example 3)

[1536] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1537] In conventional electronic payment systems, it is often difficult for users to detect input errors or missing parts, resulting in the time-consuming task of resubmitting the data. Furthermore, the lack of support tailored to the user's emotional state creates a problem of complicated procedures and increased stress, especially for users who are in a hurry or confused.

[1538] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes an automatic generation means, a multi-language support means, an automatic error check means, an emotion engine means, and a means for providing support according to the user's emotional state. This makes it possible to point out input errors and omissions in real time when the user makes an electronic payment, and to provide an appropriate support message according to the user's emotional state.

[1539] "Automatic generation means" is a function in which artificial intelligence understands the information the user needs and automatically generates the necessary form.

[1540] "Multi-language support means" refers to a function that supports users in multiple languages.

[1541] The "automatic error checking method" is a function that points out missing parts and errors in documents in real time, eliminating the need to resubmit documents.

[1542] The "emotion engine means" is a function that analyzes the user's emotional state.

[1543] The "means for providing support according to the user's emotional state" is a function that provides an appropriate support message according to the user's emotional state.

[1544] The system for implementing this invention comprises a server and a user terminal. The server includes an automatic generation means, a multi-language support means, an automatic error check means, an emotion engine means, and a means for providing support according to the user's emotional state.

[1545] A user terminal is a device such as a smartphone, tablet, or PC that a user uses to make electronic payments. The information entered by the user into the terminal is sent to the server.

[1546] The server first uses an automatic generation method to understand the information the user needs and automatically generate the necessary form using artificial intelligence. Next, an automatic error checking method points out missing parts and errors in the document in real time and prompts the user to make corrections.

[1547] Furthermore, an emotion engine means analyzes the user's emotional state. The emotion engine uses a natural language processing library such as TextBlob to detect emotions from the user's input text. Once the emotional state is detected, a support provision means according to the user's emotional state provides an appropriate support message. For example, if the user is anxious, the system will explain in simpler terms to help the user relax.

[1548] For example, if a user enters "12345abc," the server determines that the input is correct and prompts the user to proceed to the next step. If there is an input error, the emotion engine analyzes the user's emotional state and provides an appropriate support message.

[1549] Example prompts to input to a generative AI model:

[1550] Create a program that can point out input errors and omissions in real time when users are making electronic payments, and use an emotion engine to provide support based on the user's emotional state. If the user is in a hurry, the system can explain things in simpler terms to help them relax.

[1551] This allows users to make electronic payments smoothly, makes it easier to correct input errors and omissions, and provides support tailored to the user's emotional state, reducing stress and providing a more pleasant user experience.

[1552] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1553] Step 1:

[1554] The user enters electronic payment information into the terminal. The entered information is sent from the user's terminal to the server. The entered data includes the payment amount, payee, and the user's personal information.

[1555] Step 2:

[1556] The server uses an automatic generation method to understand the information the user needs and automatically generate the necessary form using artificial intelligence. The server analyzes the input data and processes it to generate an appropriate form. The generated form is then displayed to the user.

[1557] Step 3:

[1558] The user checks the generated form and enters the required information. The entered information is sent back to the server, which receives the input data and proceeds to the next processing step.

[1559] Step 4:

[1560] The server uses automated error checking to identify missing or incorrect documents in real time. It analyzes the input data and performs data calculations to detect missing or incorrect documents. If an error is detected, a message is displayed prompting the user to correct it.

[1561] Step 5:

[1562] The user makes corrections according to the error message. The corrected information is sent to the server again. The server receives the corrected data and checks the errors again.

[1563] Step 6:

[1564] The server analyzes the user's emotional state using an emotion engine means. It analyzes the user's input text and performs data calculations to detect emotions. The emotion engine uses a natural language processing library such as TextBlob.

[1565] Step 7:

[1566] The server uses a support provision method that corresponds to the user's emotional state to provide an appropriate support message. It processes data to select the message to display to the user based on the user's emotional state. For example, if the user is anxious, the system will explain in simpler terms to help the user relax.

[1567] Step 8:

[1568] The user follows the support messages to make final confirmations and corrections. If all information is correct, the payment is completed. The server receives the final data and processes the payment. The user is notified that the payment has been completed.

[1569] The above processing steps allow users to smoothly complete electronic payments, make it easy to correct input errors or omissions, and provide support tailored to the user's emotional state, reducing stress and providing a more comfortable user experience.

[1570] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1571] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1572] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1573] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1574] [Third embodiment]

[1575] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1576] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1577] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1578] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1579] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1580] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1581] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1582] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1583] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1584] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1585] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1586] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1587] "Example 1"

[1588] One aspect of the present invention is a system that includes a means for automatically generating documents required by city hall, a means for multi-language support, and a means for automatic error checking. Specifically, AI understands the information required by the user and automatically generates the required form. For example, when creating an application form required by city hall, the user inputs the required information (e.g., name, address, application details, etc.), and the AI ​​understands the information and automatically generates the appropriate form.

[1589] "Example 2"

[1590] Additionally, aspects of the present invention provide multi-language support. Specifically, regardless of the language used by the user, the system will understand that language and generate the appropriate form. For example, if the user uses English, the system will understand the information in English and generate an English form.

[1591] "Example 3"

[1592] Furthermore, aspects of the present invention provide an automated error checking mechanism. Specifically, the system identifies missing or incorrect documents in real time, eliminating the need for resubmission. For example, if a user has omitted a portion of an application form, the system will point out the missing portion and prompt the user to correct it.

[1593] The processing flow of each embodiment will be described below.

[1594] "Example 1"

[1595] Step 1: The user enters the required information into the system (e.g., name, address, application details, etc.).

[1596] Step 2: AI understands the information provided by the user and automatically generates the appropriate form.

[1597] Step 3: The generated form is presented to the user for correction and confirmation if necessary.

[1598] "Example 2"

[1599] Step 1: Enter your preferred language into the system.

[1600] Step 2: The system understands the user's language and generates the appropriate form for that language.

[1601] Step 3: The generated form is presented to the user for correction and confirmation if necessary.

[1602] "Example 3"

[1603] Step 1: The user submits the document to the system.

[1604] Step 2: The system checks the submitted documents for missing parts and errors in real time.

[1605] Step 3: If an error is detected, the system notifies the user and prompts them to correct it.

[1606] Example 1

[1607] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1608] Creating documents required by city hall is time-consuming and error-prone for users. Furthermore, the complexity increases when multilingual support is required. This often leads to users wasting time and effort by having to resubmit documents. An efficient system to solve these problems is needed.

[1609] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1610] In this invention, the server includes a means for a user to input necessary information, a means for analyzing the input information, a means for automatically generating documents based on the analysis results, a means for providing the generated documents in multiple languages, and a means for performing error checks on the generated documents. This allows users to easily create the necessary documents and provides them in multiple languages, making them usable across language barriers. Furthermore, error checks can eliminate the need for resubmission.

[1611] "User" refers to an individual or organization that uses the system to prepare the necessary documents at City Hall.

[1612] "Means for inputting information" refers to the interface that allows users to input necessary information such as name, address, and application details into the system.

[1613] "Means for analyzing information" refers to technologies, such as generative AI models, used to analyze input information and generate appropriate documents.

[1614] "Means for automatically generating documents" refers to a function that automatically creates the necessary documents based on the analyzed information.

[1615] "Means for providing in multiple languages" refers to a technology for translating the generated document into multiple languages ​​and providing it to the user.

[1616] "Means for error checking" refers to the function of checking the accuracy and appropriateness of the input content of generated documents and detecting errors.

[1617] "Generative AI model" refers to the artificial intelligence technology used to analyze user-entered information and generate appropriate documents.

[1618] "Means for verifying the existence of an address" refers to technology for verifying whether the entered address actually exists.

[1619] "Error check rules" refer to predefined criteria and conditions for verifying the appropriateness of application content.

[1620] This invention is a system for efficiently creating documents required by city hall. The system allows users to input the necessary information, analyzes that information, automatically generates appropriate documents, provides them in multiple languages, and also has the ability to check for errors.

[1621] Hardware and software used

[1622] Hardware

[1623] Server: A central processing unit for analyzing information, generating documents, translating into multiple languages, and checking for errors.

[1624] Terminal: The device (e.g., computer, smartphone) where a user enters information and reviews the resulting documents.

[1625] software

[1626] Generative AI model: An artificial intelligence technique (e.g., GPT-4) used to analyze user-entered information and generate appropriate documents.

[1627] Translation API: A service for translating generated documents into multiple languages ​​(e.g., Google Translate API).

[1628] Map API: A service that checks the existence of an entered address (e.g., Google Maps API).

[1629] Program processing

[1630] Enter user information

[1631] The user accesses the system's web interface and enters the necessary information, such as name, address, application details, etc. For example, the user enters "Taro Tanaka, Shinjuku Ward, Tokyo, application for copy of resident registration card."

[1632] Sending information

[1633] The device sends the information entered by the user to the server in JSON format. The data sent is in the following format:

[1634] json

[1635] {

[1636] "name": "Taro Tanaka",

[1637] "address": "Shinjuku-ku, Tokyo",

[1638] "application_content": "Application for a copy of residence certificate"

[1639] }

[1640] Analysis of information

[1641] The server inputs the received JSON data into a generative AI model (e.g., GPT-4), which analyzes the user's input and selects an appropriate application form template.

[1642] Generate a form

[1643] The server automatically generates an application form based on the analysis results obtained from the generative AI model. For example, it generates a form containing the necessary fields for "application for a copy of resident registration."

[1644] Multilingual support

[1645] The server translates the generated Japanese form into English and Spanish using the Google Translate API. The translated form is then provided in multiple languages, as follows:

[1646] Japanese: Application for a copy of resident registration

[1647] English: Application for a Copy of Resident Certificate

[1648] Spanish: Solicitud de Copia del Certificado de Residencia

[1649] Error Checking

[1650] The server uses the Google Maps API to verify the existence of the entered address and checks the validity of the application based on predefined rules, for example, generating an error message if the address does not exist or if the application is invalid.

[1651] Form submission

[1652] The server sends the form after error checking to the terminal. The user can review the form provided through the terminal and make corrections as necessary. For example, if the user corrects their address, the form will be checked for errors again.

[1653] Specific examples

[1654] Example 1: When a user creates an application form in Japanese

[1655] 1. The user accesses the system and enters their name, address, and application details in Japanese.

[1656] 2. The server receives the input information and analyzes it using a generative AI model (e.g., GPT-4).

[1657] 3. The server automatically generates a Japanese application form based on the analysis results.

[1658] 4. The server also translates the generated form into English using the Google Translate API.

[1659] 5. The server uses the Google Maps API to verify the existence of the address and perform other error checking.

[1660] 6. The server provides the completed error-checked form to the user.

[1661] Example 2: Example of a prompt statement

[1662] "A user enters their name, address, and application details to fill out an application form at city hall. Based on this information, please automatically generate the appropriate form and provide it in multiple languages. Please also check the input for errors."

[1663] In this way, a system is realized that allows users to easily create the documents required at city hall.

[1664] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1665] Step 1:

[1666] The user accesses the system's web interface and enters the necessary information, such as name, address, and application details. The entered information is sent from the terminal to the server. The input data is text information, such as name, address, and application details.

[1667] Step 2:

[1668] The device sends the information entered by the user to the server in JSON format. The data sent is in the following format:

[1669] json

[1670] {

[1671] "name": "Taro Tanaka",

[1672] "address": "Shinjuku-ku, Tokyo",

[1673] "application_content": "Application for a copy of residence certificate"

[1674] }

[1675] The server receives this JSON data.

[1676] Step 3:

[1677] The server inputs the received JSON data into a generative AI model (e.g., GPT-4). The generative AI model analyzes the user's input and selects an appropriate application form template. As a result of the analysis, an application form template containing the required fields is generated.

[1678] Step 4:

[1679] The server automatically generates an application form based on the analysis results obtained from the generative AI model. For example, a form containing the necessary fields for "application for a copy of resident registration" is generated. The generated form is customized based on the information entered by the user.

[1680] Step 5:

[1681] The server translates the generated Japanese form using a translation API (e.g., Google Translate API) to provide it in multiple languages. The translated form is provided in multiple languages, such as English and Spanish. For example, the Japanese "Application for a Copy of Resident Certificate" is translated into English "Application for a Copy of Resident Certificate."

[1682] Step 6:

[1683] The server performs automatic error checking on the generated form. It uses the Google Maps API to check whether the entered address exists. It also checks whether the application details are valid based on predefined rules. For example, it generates an error message if the address does not exist or if the application details are invalid.

[1684] Step 7:

[1685] The server sends the form after error checking to the terminal. The user can review the form provided through the terminal and make corrections as necessary. For example, if the user corrects their address, the form will be checked for errors again.

[1686] (Application example 1)

[1687] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1688] Autonomous vehicles require passengers to quickly and accurately prepare the necessary documents when they arrive at their destination. However, current systems require passengers to prepare the documents manually, which can lead to language barriers and errors. This can reduce passenger convenience and delay procedures at the destination. Therefore, a system is needed that automatically generates the necessary documents before passengers arrive at their destination and checks for errors in real time.

[1689] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1690] In this invention, the server includes means for automatically generating documents required by city hall, multi-language support means, automatic error checking means, means for automatically generating documents required by passengers in the infotainment system of the autonomous vehicle before they arrive at their destination, means for passengers to input required information using a smart device, and means for AI to generate appropriate documents based on the input information, thereby enabling required documents to be prepared quickly and accurately before passengers arrive at their destination.

[1691] "Means for automatically generating documents required by city hall" is a function that automatically generates various documents required by city hall based on information entered by the user.

[1692] "Multi-language support means" refers to a function that supports multiple languages ​​and translates information entered by the user into the appropriate language.

[1693] The "automatic error checking means" is a function that detects missing parts or errors in the generated document in real time and notifies the user.

[1694] An "autonomous vehicle infotainment system" is a system installed in an autonomous vehicle that provides information and entertainment to passengers.

[1695] The "means for automatically generating necessary documents before a passenger arrives at a destination" is a function for automatically generating necessary documents before a passenger arrives at a destination.

[1696] "Means for passengers to input necessary information using smart devices" refers to a function that allows passengers to input necessary information using devices such as smartphones and tablets.

[1697] "Means for AI to generate appropriate documents based on input information" refers to a function in which artificial intelligence analyzes the information input by passengers and generates appropriate documents based on that information.

[1698] A system for implementing this invention is configured as follows: First, a server includes means for automatically generating documents required by city hall, means for multi-language support, means for automatic error checking, means for automatically generating documents required by passengers in an infotainment system of an autonomous vehicle before they arrive at their destination, means for passengers to input required information using a smart device, and means for AI to generate appropriate documents based on the input information.

[1699] Hardware and Software Configuration

[1700] Hardware: Autonomous vehicle infotainment systems, smartphones, tablets, touchscreens

[1701] Software: Python, Google Translate API, Langdetect library, generative AI model

[1702] Data processing and calculation

[1703] 1. Language detection: The server detects the language of the text entered by the user using the smart device using the Langdetect library.

[1704] 2. Translation: If necessary, translate the text into the desired language using the Google Translate API.

[1705] 3. Form generation: The server automatically generates the required document form based on the information entered by the user. It uses a generative AI model to analyze the input information and generate the appropriate document.

[1706] 4. Error checking: The server detects any missing parts or errors in the generated document in real time and notifies the user.

[1707] Specific examples

[1708] For example, to generate immigration documents required for a passenger visiting Japan for tourism purposes, the following prompt sentences can be used:

[1709] Example prompt sentence:

[1710] Enter your user information:

[1711] Name: Yamada Taro

[1712] Address: Shinjuku Ward, Tokyo

[1713] Purpose: Sightseeing

[1714] By inputting this prompt into a generative AI model, the necessary documents are automatically generated. The server generates the appropriate documents based on the information entered by the user and performs error checking. This enables passengers to quickly and accurately prepare the necessary documents before arriving at their destination.

[1715] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1716] Step 1:

[1717] The user enters the required information using a smart device.

[1718] Input: A user uses a smartphone or tablet to enter information such as name, address, and purpose.

[1719] Data processing: The entered information is sent to the server.

[1720] Output: The user's input information is saved on the server.

[1721] Step 2:

[1722] The server detects the language of the input information.

[1723] Input: Text information entered by the user.

[1724] Data Computing: Detect the language of the input text using the Langdetect library.

[1725] Output: Detected language information.

[1726] Step 3:

[1727] The server translates the input information as needed.

[1728] Input: User input and detected language information.

[1729] Data processing: Use Google Translate API to translate input information into the desired language.

[1730] Output: The translated text information.

[1731] Step 4:

[1732] The server generates the required document form based on the input information.

[1733] Input: User input information (including translated information).

[1734] Data Computing: Using generative AI models to analyze input information and automatically generate appropriate document forms.

[1735] Output: The form of the generated document.

[1736] Step 5:

[1737] The server checks the generated document for errors.

[1738] Input: The form of the generated document.

[1739] Data calculation: Detect missing parts and errors in documents in real time.

[1740] Output: The result of the error check (and an error message if there is an error).

[1741] Step 6:

[1742] The server notifies the user of the results of the error check.

[1743] Input: The result of the error check.

[1744] Data processing: Generate an error message and notify the user.

[1745] Output: The error message that is displayed to the user.

[1746] Step 7:

[1747] The user corrects the error and enters the information again.

[1748] Input: The user corrects the information based on the error message and re-enters it.

[1749] Data processing: The corrected information is sent to the server again.

[1750] Output: The corrected information stored on the server.

[1751] Step 8:

[1752] The server regenerates the document based on the corrected information and checks for errors.

[1753] Input: Corrected information.

[1754] Data calculation: Regenerate documents using the AI ​​model and check for errors.

[1755] Output: A final error-free document form.

[1756] Step 9:

[1757] The server provides the final document to the user.

[1758] Input: Final document form without errors.

[1759] Data Processing: Formatting the final document for delivery to the user.

[1760] Output: The final document provided to the user.

[1761] Example 2

[1762] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1763] In the previous system, users had to manually generate forms in the language they used, making it difficult to support multiple languages. Furthermore, the system lacked the functionality to point out missing or errors in the data entered by users in real time, which resulted in the hassle of having to resubmit the form.

[1764] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for detecting the language used by the user, means for generating an appropriate form based on the detected language, means for transmitting the generated form to the user's terminal, means for receiving and processing data entered by the user, and means for transmitting the processing result to the user's terminal. This makes it easy to support multiple languages ​​and makes it possible to point out missing parts and errors in data entered by the user in real time.

[1765] "User" refers to any individual or entity that uses the System.

[1766] "Language" refers to the natural language used by the user, including English, Japanese, Spanish, and the like.

[1767] "Means for detecting" refers to technical means for identifying the language used by a user, including natural language processing techniques.

[1768] "Form" means an electronic form for a user to enter required information.

[1769] "Generating means" refers to the technical means for automatically generating the appropriate form based on the identified language.

[1770] "Means for sending" refers to the technical means for sending the generated form and processing results to the user's terminal.

[1771] "Terminal" refers to an electronic device used by a user to access the system, including a personal computer, smartphone, tablet, etc.

[1772] "Means for receiving" refers to the technical means by which the server receives the data entered by the user.

[1773] "Processing means" refers to the technical means for analysing received data and producing the required result.

[1774] A "missing portion" refers to a portion where information that should be entered by the user is missing.

[1775] "Error" refers to an error in the data entered by the user.

[1776] "Real-time" refers to processing occurring immediately as the user enters data.

[1777] "Resubmission" refers to the act of a user correcting errors or omissions and then sending the data again.

[1778] This invention is a system that automatically detects the language used by the user, generates an appropriate form, and provides it to the user. The system consists of three main elements: a server, a terminal, and a user.

[1779] The server uses natural language processing technology to detect the language used by the user, specifically using services such as Google Cloud Natural Language API and Microsoft Azure Text Analytics API. The server analyzes the user's input data and identifies the language used.

[1780] The server then generates the appropriate form based on the identified language. The server retrieves a template from the database that corresponds to the user's language and generates the form based on that template. For example, if the user speaks English, the server creates the form using the English template.

[1781] The generated form is sent from the server to the user's device. The server transmits data using the HTTP protocol, specifically through a RESTful API. The device parses the received form data and displays it in a user interface. The device renders the form using a front-end framework such as React or Vue.js.

[1782] The user enters the necessary information into the displayed form and presses the submit button. The device then generates an HTTP request again to send the data entered by the user to the server. The server processes the received data and generates the necessary results, such as saving it in a database or linking it to other services.

[1783] The processing results are sent from the server to the terminal, which then displays them to the user, allowing the user to check whether their input has been processed correctly.

[1784] As a concrete example, consider the case where a user inputs "I need a registration form" in English. The terminal sends this input data to the server, which analyzes the input data and determines that the user is using English. The server generates a registration form using an English template and sends the generated English registration form to the terminal. The terminal displays the received English registration form to the user, who enters the required information and submits it. The server processes the received data, generates a result, and sends it to the terminal, which then displays the result to the user.

[1785] An example of a prompt is as follows:

[1786] "Parse data entered by the user in English and generate an English form."

[1787] "Please parse the data entered by the user in Japanese and generate a form in Japanese."

[1788] In this way, the system can generate and present the appropriate form to the user regardless of the language the user uses.

[1789] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1790] Step 1:

[1791] The user selects or types a language.

[1792] Input: The language used by the user (e.g. English, Japanese)

[1793] How it works: The user selects the language they want to use on the system interface or enters it directly.

[1794] Output: Selected or entered language information

[1795] Step 2:

[1796] The terminal sends the user's input to the server.

[1797] Input: Language information selected or entered by the user

[1798] Operation: The terminal sends the language information selected or entered by the user to the server by generating an HTTP POST request.

[1799] Output: Language information sent to the server

[1800] Step 3:

[1801] The server detects the user's language.

[1802] Input: Language information sent to the server

[1803] How it works: The server analyzes the received data and determines the language used by the user, specifically using natural language processing techniques.

[1804] Output: Identified language information

[1805] Step 4:

[1806] The server generates the appropriate form.

[1807] Input: Identified language information

[1808] How it works: The server generates the appropriate form based on the language identified, by retrieving the corresponding template from the database and creating the form based on that template.

[1809] Output: The generated form data

[1810] Step 5:

[1811] The server sends the generated form to the terminal.

[1812] Input: Generated form data

[1813] How it works: The server sends the generated form data to the terminal, specifically via a RESTful API using the HTTP protocol.

[1814] Output: Form data sent to the terminal

[1815] Step 6:

[1816] The terminal displays the form to the user.

[1817] Input: Form data sent to the terminal

[1818] What it does: The terminal parses the received form data and displays it in a user interface, specifically by rendering the form using a front-end framework such as React or Vue.js.

[1819] Output: The form displayed to the user

[1820] Step 7:

[1821] The user fills in the required information in the form and submits it.

[1822] Input: Information entered by the user (e.g., name, email address)

[1823] How it works: The user enters the required information into the displayed form and presses the submit button.

[1824] Output: The information entered

[1825] Step 8:

[1826] The terminal sends the input data to the server.

[1827] Input: Information entered

[1828] Operation: The terminal generates an HTTP POST request to send the data entered by the user to the server.

[1829] Output: The input data sent to the server

[1830] Step 9:

[1831] The server processes the input data and produces a result.

[1832] Input: Input data sent to the server

[1833] Operation: The server analyzes the received data and generates the necessary results, such as storing them in a database or connecting to other services.

[1834] Output: Generated result data

[1835] Step 10:

[1836] The server sends the results to the terminal.

[1837] Input: Generated result data

[1838] Operation: The server sends the generated result data to the terminal. Specifically, it sends the data in JSON format again via the RESTful API.

[1839] Output: Result data sent to the terminal

[1840] Step 11:

[1841] The terminal displays the results to the user.

[1842] Input: Result data sent to the terminal

[1843] How it works: The device parses the result data received from the server and displays it in the user interface. Specifically, it uses React to render the results.

[1844] Output: The result displayed to the user

[1845] (Application example 2)

[1846] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1847] With the previous system, it was difficult to automatically generate the appropriate form according to the user's language, which led to a poor user experience, especially in environments where multilingual support was required. Furthermore, the system lacked the functionality to point out missing or incorrect documents in real time, which often required users to resubmit documents.

[1848] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an automatic document generation means, a multi-language support means, an automatic error check means, a means for detecting the user's input language, and a means for generating an appropriate form based on the detected language. This makes it possible to automatically generate an appropriate form according to the language used by the user, and by pointing out missing parts and errors in the document in real time, it becomes possible to eliminate the need for resubmission.

[1849] "Automatic document generation means" is a function that automatically creates appropriate documents and forms based on the information required by the user.

[1850] "Multi-language support means" refers to a function that supports multiple languages ​​used by users and provides appropriate information in each language.

[1851] "Automatic error checking means" is a function that detects missing parts and errors in documents in real time and points them out to the user.

[1852] A "means for detecting the user's input language" is a function that automatically identifies the language of text entered by the user.

[1853] The "means for generating an appropriate form based on the detected language" is a function that automatically generates an appropriate form in a language that the user can easily understand, depending on the detected language.

[1854] A system for implementing the present invention includes means for automatically generating documents, means for multi-language support, means for automatic error checking, means for detecting a user's input language, and means for generating an appropriate form based on the detected language.

[1855] The server uses a language detection library (e.g., langdetect) to automatically identify the language of the text entered by the user. If the text entered by the user is Japanese, it generates a Japanese form, and if it is English, it generates an English form. This process involves using Google's translation API (googletrans library) to translate the text if necessary.

[1856] Specifically, if a user types "search for products" on a smartphone, the server receives this input and uses a language detection library to identify that it is in Japanese. It then generates a Japanese form and provides it to the user, allowing the user to search for products in their own language and proceed with the purchase process.

[1857] The server also uses automated error checking to detect missing or incorrect parts of the generated form in real time and notify the user, saving the user the trouble of having to resubmit the form.

[1858] The hardware used is a smartphone, and the software is Python, the langdetect library, and the googletrans library.

[1859] For example, if a user types "Search for products", a Japanese form will be generated. An example of this prompt is:

[1860] If a user types "Search for products", generate a form in Japanese.

[1861] In this way, it is possible to automatically generate the appropriate form according to the language used by the user, and by pointing out missing parts or errors in the document in real time, it is possible to eliminate the need to resubmit the form.

[1862] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1863] Step 1:

[1864] A user uses a smartphone to input text, for example, "Search for a product." This input text is sent to the system.

[1865] Step 2:

[1866] The server analyzes the received input text using a language detection library (langdetect) to identify the language of the input text. The input is the user's text, and the output is the identified language (Japanese in this case).

[1867] Step 3:

[1868] The server generates an appropriate form based on the identified language, where templates for form generation are available and a template is selected depending on the language, the input is the identified language, and the output is the generated form.

[1869] Step 4:

[1870] The server sends the generated form to the user's smartphone, where the user can view the form displayed in their own language. The input is the generated form, and the output is the form displayed on the user's smartphone.

[1871] Step 5:

[1872] The user fills in the form and presses the submit button. The entered data is sent to the server. The input is the data the user entered into the form, and the output is the data sent to the server.

[1873] Step 6:

[1874] The server uses automatic error checking to detect missing or erroneous data in real time. The input is the data sent by the user, and the output is any detected errors.

[1875] Step 7:

[1876] The server notifies the user of the detected error information. The user receives instructions for correcting the error, and can correct the form again and submit it. The input is the detected error information, and the output is the error information notified to the user.

[1877] Step 8:

[1878] The user corrects the errors and submits the form again. The server receives the data again and checks for errors. If there are no errors, the data is processed successfully. The input is the corrected data, and the output is the successfully processed data.

[1879] In this way, an appropriate form is automatically generated according to the language used by the user, and error checking is performed in real time.

[1880] Example 3

[1881] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1882] Conventional document submission systems required users to manually check and correct missing or incorrect documents, resulting in time-consuming resubmissions. Furthermore, they lacked multilingual support, making them difficult for users who speak different languages. Furthermore, they lacked the technology to accurately analyze document content, resulting in low error detection accuracy.

[1883] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1884] In this invention, the server includes an automatic document generation means, a multilingual support means, an automatic error check means, an optical character recognition means, an analysis means using a generative AI model, and a real-time notification means. This allows missing parts and errors in documents submitted by users to be detected in real time and prompt corrections to be made. Multilingual support also makes it easy for users who speak different languages ​​to use the system. Furthermore, analysis using a generative AI model allows for highly accurate analysis of the document contents, improving the accuracy of error detection.

[1885] "Automatic document generation means" is a function that automatically generates the necessary forms based on the information required by the user.

[1886] "Multilingual support means" refers to a function that provides system functions and interfaces in multiple languages ​​to users who speak different languages.

[1887] "Automatic error checking means" is a function that detects missing parts or errors in submitted documents in real time and notifies the user.

[1888] "Optical character recognition means" is a technology for converting uploaded documents into text data.

[1889] "Analysis means using a generative AI model" is a function that uses a generative AI model to analyze text data and understand the contents of a document.

[1890] "Real-time notification means" is a function that immediately notifies the user of detected missing parts or errors.

[1891] This invention is a system that detects missing parts and errors in documents submitted by users in real time and prompts them to correct them quickly. The system includes an automatic document generation means, a multilingual support means, an automatic error check means, an optical character recognition means, an analysis means using a generative AI model, and a real-time notification means.

[1892] First, the user accesses the system interface using a terminal and uploads documents such as application forms. The documents to be uploaded are in PDF or image format. The server receives the documents uploaded by the user and temporarily stores them on the server.

[1893] The server then uses optical character recognition (e.g., Tesseract OCR) to convert the uploaded document into text data, which converts images and PDF documents into parseable text data.

[1894] The server uses a generative AI model (e.g., OpenAI GPT-4) to analyze the converted text data. The goal of the analysis is to understand the content of the document and identify gaps and errors. Examples of prompts to input to the generative AI model include:

[1895] Analyze the application submitted by the user to detect missing parts and errors. Analyze the following text data:

[1896] [Text data]

[1897] The server uses the results of the generative AI model's analysis to detect missing parts and errors in the document, such as missing required fields or incorrect formatting.

[1898] Any missing or errors detected are notified to the user using real-time notification methods. Notifications are displayed in real time on the system interface, and can also be sent by email or other means if necessary.

[1899] For example, suppose a user uploads a mortgage application. The application is missing the annual income field. When the user uploads the application, the server receives the document and converts it into text data using Tesseract OCR. Next, it analyzes the text data using a generative AI model (e.g., OpenAI GPT-4) and detects that the annual income field is missing. Based on this information, the server notifies the user, "The annual income field is missing. Please correct it." The user receives this notification, fills in the annual income field, and uploads the application again.

[1900] In this way, users can quickly correct missing parts and errors in documents, eliminating the need to resubmit them. Multilingual support also makes it easy for users who speak different languages ​​to use the system. Furthermore, analysis using a generative AI model enables highly accurate analysis of document content, improving the accuracy of error detection. The flow of the identification process in Example 3 will be described with reference to FIG. 15.

[1901] Step 1:

[1902] User uploads document

[1903] Users access the system interface using a terminal and upload documents such as application forms. The input is documents in PDF format or image format, and the output is the document data sent to the server.

[1904] Step 2:

[1905] The server receives the document

[1906] The server receives the document uploaded by the user and temporarily stores it in the server. The input is the document data sent by the user, and the output is the document data stored in the server.

[1907] Step 3:

[1908] The server converts the document into text data using OCR software.

[1909] The server converts the uploaded document into text data using optical character recognition (e.g., "Tesseract OCR"). The input is the document data stored on the server, and the output is text data. Specifically, the OCR software analyzes the document image and extracts the text information.

[1910] Step 4:

[1911] The server analyzes the text data using a generative AI model

[1912] The server uses a generative AI model (such as OpenAI GPT-4) to analyze the converted text data. The input is the text data, and the output is the analysis result. Specifically, the generative AI model analyzes the text data based on the prompt and understands the content of the document.

[1913] Step 5:

[1914] The server detects missing parts and errors based on the analysis results.

[1915] The server detects missing parts and errors in documents based on the analysis results of the generative AI model. The input is the analysis results, and the output is a list of missing parts and errors. Specifically, it collates the analysis results and identifies missing required fields and formatting errors.

[1916] Step 6:

[1917] The server notifies the user of any missing parts or errors

[1918] The server notifies the user of any missing parts or errors that it detects. The input is a list of missing parts or errors, and the output is a notification message to the user. Specifically, the server displays a notification in real time on the system interface and notifies the user by email or other means if necessary.

[1919] Step 7:

[1920] The user corrects the document and resubmits it

[1921] The user receives a notification from the server and corrects any missing parts or errors that have been pointed out. After the corrections are complete, the user uploads the document again and resubmits it. The input is the notification message from the server, and the output is the corrected document data. Specifically, the user corrects the document and uploads it to the system again.

[1922] (Application example 3)

[1923] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1924] The existing system lacked the ability to automatically generate documents required by city hall or to support multiple languages. Furthermore, it lacked the functionality to point out missing or incorrect documents in real time, forcing users to go through the trouble of resubmitting them. Furthermore, there was a problem with missing or incorrect information being easily input when entering electronic payment information, which led to frequent payment errors. A system that could solve these issues was needed.

[1925] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1926] In this invention, the server includes a means for automatically generating documents required by the city hall, a multi-language support means, an automatic error checking means, and a means for pointing out missing or error parts in electronic payment information in real time and prompting the user to correct them. This makes it possible to point out missing or error parts in documents in real time and eliminate the need for resubmission. Furthermore, when inputting electronic payment information, missing or error parts are pointed out in real time and the user is prompted to correct them, thereby reducing payment errors.

[1927] A "city hall" is an administrative agency of a local government and a facility that provides various administrative services to citizens.

[1928] An "automatic document generation means" is a system that has the function of automatically creating the necessary documents and forms based on the information required by the user.

[1929] "Multi-language support means" means a system that supports multiple languages ​​and has the ability to provide information in the language selected by the user.

[1930] An "automatic error checking means" is a system that has the function of detecting missing parts or errors in documents or input information in real time and prompting the user to make corrections.

[1931] "Electronic Payment Information" refers to information such as credit card information, address, and name required for online payments.

[1932] A "missing portion" refers to a portion where necessary information has not been entered.

[1933] An "error" is when the information entered is incorrect or out of format.

[1934] "Real-time" refers to immediate processing and feedback as users input information.

[1935] "User" refers to any individual or entity that uses the System.

[1936] "Encouraging correction" means pointing out any errors or omissions in the information entered to the user and asking them to re-enter the correct information.

[1937] A system for implementing this invention includes a server, a user terminal, and a network. The server includes a means for automatically generating documents required by the city hall, a multi-language support means, an automatic error checking means, and a means for pointing out missing or errors in electronic payment information in real time and prompting the user to correct them.

[1938] A user terminal is a device such as a smartphone, tablet, or PC that provides an interface for users to input information. Once the user uses the terminal to input the required information, the information is sent to the server.

[1939] The server first receives the information entered by the user and then uses an automated document generation method to automatically create the necessary documents and forms, using a generative AI model to analyze the user's input and generate the appropriate documents.

[1940] Multi-language support is then used to provide information in the user's language of choice, thereby accommodating users who speak different languages.

[1941] Additionally, automated error checking measures are used to detect missing or incorrect information entered by the user in real time, such as checking that credit card numbers, expiration dates, security codes, names, addresses, etc. If an error is detected, the server provides immediate feedback to the user to prompt them to make corrections.

[1942] As a concrete example, consider the case where a user leaves out part of the card number when entering credit card information. In this case, the server displays an error message saying "The credit card number is invalid" and asks the user to re-enter the correct information.

[1943] Example prompts to input to a generative AI model:

[1944] Write a program that checks the credit card information entered by the user and points out any missing or incorrect information in real time. Check the following fields: credit card number, expiration date, security code, name, and address. If there are any errors in each field, add the errors to a list and provide feedback to the user.

[1945] This system can point out missing or errors in documents in real time, eliminating the need for resubmission. It can also point out missing or errors in electronic payment information entry in real time and prompt users to correct them, reducing payment errors.

[1946] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1947] Step 1:

[1948] The user uses the terminal to enter the required information.

[1949] Input: Information entered by the user through the device interface (e.g., credit card number, expiration date, security code, name, address).

[1950] Output: The entered information is sent from the terminal to the server.

[1951] Step 2:

[1952] The server analyzes the received information and automatically creates the necessary documents and forms using an automatic document generation means.

[1953] Input: User input sent from the device.

[1954] Data processing: Using generative AI models to analyze user input and generate appropriate documents.

[1955] Output: The generated documents or forms.

[1956] Step 3:

[1957] The server uses multi-language support to provide information in the language selected by the user.

[1958] Input: User input and language selection.

[1959] Data processing: Translate information based on the selected language and provide it to the user.

[1960] Output: Information displayed in the user's language of choice.

[1961] Step 4:

[1962] The server uses automated error checking measures to detect missing or incorrect information entered by the user in real time.

[1963] Input: User input information.

[1964] Data processing: Use regular expressions and other validation algorithms to detect missing or error information in input.

[1965] Output: A list of detected errors and omissions.

[1966] Step 5:

[1967] The server provides feedback to the user to prompt them to correct any errors or omissions it detects.

[1968] Input: A list of detected errors and omissions.

[1969] Data processing: Generate an error message and display it to the user.

[1970] Output: The error message that is displayed to the user.

[1971] Step 6:

[1972] The user corrects the information based on the error message and re-enters it.

[1973] Input: User-modified information.

[1974] Output: The corrected information is sent to the server again.

[1975] Step 7:

[1976] The server parses the information again to ensure there are no errors.

[1977] Input: Corrected information.

[1978] Data processing: Validate input information again using regular expressions or other validation algorithms.

[1979] Output: If there are no errors, processing is complete. If there are errors, go back to step 5 again.

[1980] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1981] "Example 1"

[1982] One embodiment of the present invention provides a system incorporating an emotion engine. This system recognizes a user's emotions and adjusts its operation according to the user's emotional state. Specifically, if the system recognizes that the user is feeling stressed, it adjusts the operation of the automatic generation means and automatic error checking means to reduce the user's stress. For example, the system may change the way error messages are displayed to a gentler tone or automatically generate the necessary documents more smoothly.

[1983] "Example 2"

[1984] The emotion engine also recognizes users' feelings of joy and satisfaction and uses that information to improve system performance. For example, if the system recognizes that a user is satisfied with the automated generation of a particular form, it can learn how to generate that form and improve form generation in similar situations.

[1985] "Example 3"

[1986] Furthermore, the emotion engine also adjusts the operation of the multi-language support measures according to the user's emotional state. For example, if the system recognizes that the user is confused, it will strengthen support in the user's native language. This allows the user to receive support in their own language, clear up their confusion, and smoothly proceed with completing the necessary documents.

[1987] The processing flow of each embodiment will be described below.

[1988] "Example 1"

[1989] Step 1: The system recognizes the user's emotions using an emotion engine.

[1990] Step 2: If the emotion engine recognizes the user's stress, the system adjusts the behavior of the automatic generation and error checking measures.

[1991] Step 3: Specifically, we will change the way error messages are displayed to a gentler tone and make the automatic generation of necessary documents smoother.

[1992] "Example 2"

[1993] Step 1: The emotion engine recognizes the user's joy or satisfaction.

[1994] Step 2: If the user recognizes that they are happy with the auto-generation of a particular form, the system learns how to generate that form.

[1995] Step 3: Use the learned information to improve form generation in similar situations.

[1996] "Example 3"

[1997] Step 1: The emotion engine adjusts the behavior of the multi-language support means according to the user's emotional state.

[1998] Step 2: If the system recognizes that the user is confused, it will provide more support in the user's native language.

[1999] Step 3: This allows users to receive support in their own language, clearing up any confusion and facilitating the creation of the necessary documents.

[2000] Example 1

[2001] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2002] Creating documents required by city hall is a cumbersome and time-consuming process for users. Furthermore, when multilingual support is required or when document error checking is required, the process becomes even more time-consuming. Furthermore, users may find it difficult to operate the system in stressful situations. An efficient system that can solve these problems is needed.

[2003] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes an automatic generation means, a multilingual support means, an automatic error check means, an emotion recognition means, a user information input means, an information transmission means, and a feedback provision means. This makes it possible to quickly and accurately automatically generate documents required by the user, support multiple languages, perform error checks, and further adjust the operation of the system according to the user's emotional state.

[2004] "Automatic generation means" is a function that automatically generates necessary documents and forms based on information entered by the user.

[2005] "Multilingual support means" is a function that translates generated documents and forms into multiple languages ​​and provides them in the language selected by the user.

[2006] "Automatic error checking means" is a function that automatically detects missing parts and errors in generated documents and forms and points them out in real time.

[2007] "Emotion recognition means" is a function that analyzes the user's emotional state and adjusts the system's operation according to that emotional state.

[2008] "User information input means" is a function that provides an interface for the user to input necessary information.

[2009] "Information transmission means" is a function that transmits information entered by the user to the server.

[2010] The "feedback providing means" is a function that displays information and error messages received from the server to the user and provides necessary feedback.

[2011] MODE FOR CARRYING OUT THE INVENTION

[2012] The present invention is a system for automatically generating documents required by city hall, and aims to quickly and accurately generate the necessary documents and forms based on information entered by the user. This system includes an automatic generation means, a multilingual support means, an automatic error check means, an emotion recognition means, a user information input means, an information transmission means, and a feedback provision means.

[2013] Hardware and software used

[2014] Hardware: The device (e.g., PC, smartphone, tablet) through which the user enters information and the server that processes the information.

[2015] Software: Generative AI models (e.g., OpenAI's GPT-4), translation software (e.g., Google Translate API), emotion recognition AI models, and rule-based error-checking algorithms.

[2016] Program processing

[2017] 1. Enter your user information

[2018] The user uses the terminal to enter the necessary information (e.g., name, address, application details, etc.).

[2019] The terminal temporarily stores the entered information and prepares it for the next processing step.

[2020] 2. Transmission of information

[2021] The device sends the saved user information to the server.

[2022] The server analyzes the received information and converts it into the required data format.

[2023] 3. Information Understanding and Automatic Form Generation

[2024] The server generates prompt sentences to input the received information into the generative AI model.

[2025] The server sends prompts to the generative AI model, which then automatically generates the appropriate form.

[2026] The generative AI model generates the required document form based on the prompt sentence and returns it to the server.

[2027] 4. Multilingual support

[2028] The server checks the user's language preference.

[2029] The server translates the generated form using translation software to make it multilingual.

[2030] The server sends the translated form to the terminal.

[2031] 5. Automatic Error Checking

[2032] The server validates the entered information and generated forms with automated error checking.

[2033] If an error is detected, the server generates an error message and sends it to the terminal.

[2034] 6. Emotional engine for behavior adjustment

[2035] The server analyzes the user's emotional state using an emotion recognition AI model.

[2036] If the server detects that the user is stressed, it will change the tone of the error message to be gentler.

[2037] The server will make adjustments as necessary to smooth the form generation process.

[2038] 7. Providing Feedback

[2039] The terminal displays the final form and any error messages received from the server to the user.

[2040] The user checks the displayed information and corrects or re-enters it as necessary.

[2041] Specific examples

[2042] For example, consider the case where a user applies for a copy of their resident registration card at city hall. The user enters their name "Yamada Taro," their address "Shinjuku Ward, Tokyo," and the request for a copy of their resident registration card into their device. The device then sends this information to the server. The server then sends the following prompt to the generative AI model:

[2043] Generate a form for a user to apply for a copy of their resident registration card at city hall. The user's name is "Yamada Taro," their address is "Shinjuku-ku, Tokyo," and the request is for a copy of their resident registration card.

[2044] The generative AI model generates an application form for a copy of the resident registration certificate based on this prompt and returns it to the server. The server translates the form using the Google Translate API to make it multilingual and performs error checking. If an error is detected, the emotion engine recognizes the user's stress and generates a gentle error message. Finally, the device displays the generated form and error message to the user.

[2045] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2046] Step 1: Enter your user information

[2047] The user uses the terminal to enter the necessary information (e.g., name, address, application details, etc.).

[2048] Input: Information entered by the user (name, address, application details).

[2049] The terminal temporarily stores the entered information and prepares it for the next processing step.

[2050] Output: Saved user information.

[2051] Step 2: Submit your information

[2052] The device sends the saved user information to the server.

[2053] Input: Saved user information.

[2054] The server analyzes the received information and converts it into the required data format.

[2055] Output: Parsed user information.

[2056] Step 3: Understanding the information and automatically generating the form

[2057] The server generates prompt sentences to input the received information into the generative AI model.

[2058] Input: Parsed user information.

[2059] The server sends prompts to the generative AI model, which then automatically generates the appropriate form.

[2060] The generative AI model generates the required document form based on the prompt sentence and returns it to the server.

[2061] Output: The generated form.

[2062] Step 4: Multilingual support

[2063] The server checks the user's language preference.

[2064] Input: Generated form, user language preference.

[2065] The server translates the generated form using translation software to make it multilingual.

[2066] The server sends the translated form to the terminal.

[2067] Output: The translated form.

[2068] Step 5: Automatic error checking

[2069] The server validates the entered information and generated forms with automated error checking.

[2070] Input: translated form, user information.

[2071] If an error is detected, the server generates an error message and sends it to the terminal.

[2072] Output: Error message (if necessary).

[2073] Step 6: Adjusting behavior with the emotion engine

[2074] The server analyzes the user's emotional state using an emotion recognition AI model.

[2075] Input: The user's emotional state.

[2076] If the server detects that the user is stressed, it will change the tone of the error message to be gentler.

[2077] The server will make adjustments as necessary to smooth the form generation process.

[2078] Output: Adjusted error messages, smoother form generation process.

[2079] Step 7: Provide feedback

[2080] The terminal displays the final form and any error messages received from the server to the user.

[2081] Input: Final form, error messages.

[2082] The user checks the displayed information and corrects or re-enters it as necessary.

[2083] Output: User confirmation and correction information.

[2084] (Application example 1)

[2085] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referr...

Claims

1. A means for obtaining information entered by a user; means for generating a form in a predetermined language using a generative AI model based on the information; means for translating the generated form into a language different from the predetermined language; A means for performing an error check based on predefined rules to check whether the content of the generated form is appropriate; A system including:

2. A means for obtaining information entered by a user; means for detecting a language used by said user based on said information; means for generating a form in the detected language using a generative AI model based on the information; means for transmitting the generated form to the user; A system including:

3. means for obtaining text entered by a user; means for identifying the language of said text; means for generating a form in the same language as the identified language; means for performing an error check on the contents entered in the form and notifying the user of detected errors; A system including:

Images