System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a document; means for extracting character information using optical character recognition technology; means for analyzing the extracted information and performing a plurality of accounting standards and tax decisions; means for referring to accounts set for each company and proposing an appropriate account; means for presenting the proposed account to a user and allowing the user to confirm and correct the account; means for collating with related documents and automatically inputting transaction information; means for transmitting integrated transaction information to an external accounting system; and means for notifying the user of the transmission result.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] Accounting work typically requires a great deal of time and effort, and tasks such as reading contracts and purchase orders, organizing information, applying accounting items, and making tax decisions are particularly tedious. This places a heavy burden on the person in charge and necessitates time-consuming manual work. Furthermore, human error and reduced work efficiency when entering data into accounting systems are also problems. There is a need to solve these problems and achieve efficient and accurate accounting operations. [Means for solving the problem]

[0005] The system of the present invention solves the above problems by including the following components.

[0006] The system includes a means for receiving documents, a means for extracting character information using optical character recognition technology, a means for analyzing the extracted information and making multiple accounting standards and tax decisions, a means for referencing account items set for each company and proposing appropriate account items, a means for presenting the proposed account items to a user and allowing the user to confirm and correct them, a means for comparing with related documents and automatically inputting transaction information, a means for transmitting the integrated transaction information to an external accounting system, and a means for notifying the user of the transmission results.Furthermore, by including a means for automatically identifying the type of document and selecting the appropriate processing procedure and a means for improving the accuracy of the extracted information using natural language processing technology, the system achieves more accurate and efficient automation of accounting work.

[0007] "Documents" refers to documents such as contracts, purchase orders, and invoices related to accounting work.

[0008] "Means for receiving" refers to the function for importing documents uploaded by users into the system.

[0009] "Optical character recognition technology" refers to technology that extracts character information from image data.

[0010] "Text information" refers to text data read from a document using optical character recognition technology.

[0011] "Means for extracting" refers to the ability to extract the required information from a document using optical character recognition technology.

[0012] "Analyzing" refers to analyzing the extracted information and organizing it into meaningful data.

[0013] "Accounting standards" refer to the rules and guidelines for accurately recording and reporting financial transactions.

[0014] "Tax judgment" refers to a judgment on taxation or deduction made based on tax law.

[0015] "Account item" refers to the category name used to classify transactions in an accounting system.

[0016] "Means for suggesting" refers to the function of presenting appropriate account items to the user based on the analyzed information.

[0017] "Means of matching" refers to the function of comparing existing related documents with newly imported documents to confirm a match.

[0018] "Means for automatic input" refers to the function by which the system automatically inputs the necessary data based on the matching results.

[0019] "Means for transmitting" refers to the ability of the system to send integrated transaction information to an external accounting system.

[0020] "Means for notifying" refers to a function for notifying the user of the results of data transmission and the processing status.

[0021] "Automatically identifying document type" refers to automatically determining whether the uploaded document belongs to a specific type, such as a contract or purchase order.

[0022] "Natural language processing technology" refers to technology that enables computers to understand and process human language. [Brief explanation of the drawings]

[0023] [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. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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, a 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), and an APU (Accelerated Processing Unit).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. 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."

[0044] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[0045] System Operation Overview

[0046] 1. Upload your documents

[0047] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[0048] 2. Document sorting and OCR processing

[0049] The server receives documents uploaded by users and stores them in temporary storage.

[0050] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[0051] The server sends the identified documents to an AI-OCR engine to extract the text information.

[0052] 3. Information analysis and extraction

[0053] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[0054] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[0055] 4. Clarifying accounting and tax issues

[0056] The server makes multiple accounting and tax decisions based on the stored data.

[0057] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[0058] 5. Account suggestion

[0059] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0060] The server displays the proposed account items on the user's operation screen.

[0061] The user can review the proposed accounts and approve or modify them as needed.

[0062] 6. Document verification and entry

[0063] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[0064] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[0065] 7. Send to accounting system

[0066] The server transmits the final transaction information in a consistent state to the external accounting system.

[0067] The server checks whether the transmission was successful and notifies the user of the result.

[0068] Specific examples

[0069] Contract processing example

[0070] 1. The user scans the contract and saves it in PDF format on their device.

[0071] 2. The user opens the system's upload function and uploads the saved contract to the server.

[0072] 3. The server receives the uploaded contract and stores it in temporary storage.

[0073] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[0074] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[0075] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[0076] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[0077] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[0078] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[0079] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0080] 11. The server checks whether the transmission was successful and notifies the user of the result.

[0081] In this way, the system of the present invention significantly improves the efficiency of accounting work and enables accurate accounting processing.

[0082] The processing flow will be explained below.

[0083] Step 1:

[0084] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[0085] Step 2:

[0086] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[0087] Step 3:

[0088] The server receives the uploaded documents and stores them in temporary storage.

[0089] Step 4:

[0090] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[0091] Step 5:

[0092] The server sends the identified documents to the AI-OCR engine to extract the text information.

[0093] Step 6:

[0094] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[0095] Step 7:

[0096] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[0097] Step 8:

[0098] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[0099] Step 9:

[0100] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0101] Step 10:

[0102] The server displays the selected account items on the user's operation screen.

[0103] Step 11:

[0104] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[0105] Step 12:

[0106] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[0107] Step 13:

[0108] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[0109] Step 14:

[0110] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0111] Step 15:

[0112] The server checks whether the transmission was successful and notifies the user of the result.

[0113] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders.

[0114] Example 1

[0115] Next, a description will be given of 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."

[0116] In accounting work, it is common to manually process documents such as contracts and purchase orders, which requires a great deal of time and effort. Manual data entry is prone to human error, which can lead to inaccurate accounting and tax decisions. Furthermore, efficient processing of vast amounts of accounting documents and accurate accounting procedures requires advanced technology, which places a heavy burden on many companies.

[0117] 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.

[0118] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for temporarily storing uploaded documents, means for transmitting to a corresponding optical character recognition engine based on the automatically identified documents, means for analyzing and parsing important information using natural language processing technology, and means for referencing a relational database that stores analyzed information each time. This enables automatic processing of accounting documents, thereby improving processing efficiency and accuracy.

[0119] The "means for receiving documents" is a function for receiving accounting documents uploaded by users and temporarily storing them.

[0120] "Optical character recognition technology" is a technology that automatically extracts text information from documents stored in digital formats such as images and PDFs.

[0121] The "means for analyzing extracted information" is a function for analyzing extracted character information using optical character recognition technology and extracting necessary data.

[0122] "Means for making multiple accounting standards and tax decisions" refers to a function that automatically makes various accounting standards and tax decisions based on extracted and analyzed data.

[0123] "Means for referencing account items set for each company" refers to a function for referencing an account item chart customized for each company and selecting appropriate account items.

[0124] The "means for proposing appropriate account items" is a function for proposing the most appropriate account items based on the analyzed information.

[0125] The "means for presenting the proposed account items to the user" is a function for displaying the selected account items to the user and enabling confirmation and correction.

[0126] "Means for user confirmation and correction" is a function that allows users to check the proposed account items and correct them if necessary.

[0127] "Means for comparing with related documents and automatically inputting transaction information" is a function for comparing existing related documents with uploaded documents and automatically inputting transaction information.

[0128] The "means for transmitting integrated transaction information to an external accounting system" is a function for transmitting the final integrated transaction information in a predetermined format to an external accounting system.

[0129] The "means for notifying the user of the transmission result" is a function for checking whether the data transmission to the external accounting system was successful and notifying the user of the result.

[0130] The "means for temporarily storing uploaded documents" is a function for temporarily storing documents uploaded by users in cloud storage or the like.

[0131] The "means for transmitting to a corresponding optical character recognition engine based on the automatically identified document" is a function for transmitting data to an appropriate optical character recognition engine depending on the type of automatically identified document.

[0132] "Means for analyzing and interpreting important information using natural language processing technology" refers to a function that uses natural language processing technology to accurately analyze important information from extracted text data.

[0133] "Means for referencing the relational database that stores analyzed information each time" refers to a function for referencing the relational database that stores analyzed information each time and retrieving the necessary data at the appropriate time.

[0134] The system of the present invention automatically processes accounting documents, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[0135] System Overview

[0136] This system is primarily composed of a server, user devices, and several software components. The server receives accounting documents, stores them, processes them with OCR, analyzes the information, proposes account items, collates documents, and sends the data to the accounting system. The user device scans accounting documents and uploads them to the system. The specific usage of each piece of hardware and software is explained below.

[0137] Document upload

[0138] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). Then, they open the system interface, select the digitized document file (PDF or image format), and click the upload button. The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3).

[0139] Document sorting and OCR processing

[0140] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). Based on the identification results, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The extracted text data is stored in a temporary database (e.g., MongoDB).

[0141] Information analysis and extraction

[0142] The server extracts the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The extracted important information is stored in a relational database (e.g., MySQL).

[0143] Clarifying accounting and tax issues

[0144] The server uses the stored data to make accounting and tax decisions, such as whether consumption tax applies, whether payment is made in advance or later, and whether payment is due, using a specific software library (e.g., PyDSTool).

[0145] Account suggestion

[0146] The server references a custom chart of accounts (e.g., a QuickBooks account list) configured for each company. Based on the analyzed information, it recommends appropriate accounts and displays them on the user's screen. The user can review the recommended accounts and modify or approve them as necessary.

[0147] Document verification and entry

[0148] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered to complete the required information.

[0149] Send to accounting system

[0150] The server finally converts the organized transaction information into the format of the ERP system (e.g., SAP ERP), sends the converted data to the external accounting system, checks the transmission results, and finally notifies the user of the transmission results.

[0151] Specific examples

[0152] Contract processing example

[0153] 1. The user scans the contract and saves it on their device.

[0154] 2. The user opens the system interface and uploads the contract file.

[0155] 3. The server receives the file and temporarily stores it in cloud storage.

[0156] 4. The server automatically identifies the file type as a contract using the cloud service API.

[0157] 5. The server sends the file to the OCR engine and extracts the character data.

[0158] 6. The server stores the extracted data in a temporary database.

[0159] 7. The server analyzes the data using natural language processing libraries and stores important information in a relational database.

[0160] 8. The server organizes accounting and tax standards and automatically determines tax issues.

[0161] 9. The server consults the chart of accounts and recommends the most appropriate accounts to the user.

[0162] 10. The user reviews the proposed accounts and makes any necessary modifications.

[0163] 11. The server compares the contract with other related documents and automatically fills in the required information.

[0164] 12. The server converts the data into ERP format and sends it to the accounting system.

[0165] 13. The server checks the transmission result and notifies the user.

[0166] Prompt Sentence Examples

[0167] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[0168] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[0169] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0170] Program processing steps

[0171] Step 1:

[0172] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). They select the digitized file (PDF or image format) in the system interface and click the upload button. The input is the physical file of the accounting document, and the output is the digital file saved on their device.

[0173] Step 2:

[0174] The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3). The input is the uploaded digital file, and the output is the file stored in the cloud storage.

[0175] Step 3:

[0176] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). The input is the file stored in cloud storage, and the output is the document type identification result. Based on the identification result, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The input is the document type and file, and the output is the extracted text data.

[0177] Step 4:

[0178] The server stores the character data obtained by OCR processing in a temporary database (e.g., MongoDB). The input is the character data extracted by OCR processing, and the output is the data stored in the temporary database.

[0179] Step 5:

[0180] The server takes the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The input is the stored text data, and the output is the analyzed important information. The extracted important information is stored in a relational database (e.g., MySQL). Specifically, the server uses SpaCy to tokenize the text data and applies a specific pattern matching algorithm.

[0181] Step 6:

[0182] The server uses the stored data to make accounting and tax decisions. For example, it uses a specific software library (e.g., PyDSTool) to perform automated decisions such as whether consumption tax applies or confirming payment due dates. The input is data stored in a relational database, and the output is the accounting and tax decisions.

[0183] Step 7:

[0184] The server references a custom chart of accounts configured for each company (e.g., a custom list of accounts in accounting software). The input is the parsed information and the chart of accounts, and the output is the recommendation of the best accounts. Specifically, the server reads the chart of accounts from the database and runs an algorithm to select the appropriate accounts.

[0185] Step 8:

[0186] The server displays the recommended accounts on the user's screen, and the user can review, modify, and approve them as necessary. The input is the recommended accounts, and the output is the accounts confirmed by the user.

[0187] Step 9:

[0188] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered and necessary information is completed. The input is the related documents and analyzed information, and the output is the completed transaction information.

[0189] Step 10:

[0190] The server finally converts the organized transaction information into the format of an ERP system (e.g., enterprise resource planning software). It then sends the converted data to an external accounting system and checks the transmission result. The input is the completed transaction information, and the output is the data converted into the ERP format and the transmission result. Finally, it notifies the user of the transmission result.

[0191] Prompt Sentence Examples

[0192] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[0193] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[0194] (Application example 1)

[0195] Next, a description will be given of Application 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."

[0196] Modern logistics centers handle a large number of delivery notes and invoices every day, and manually processing these documents requires a huge amount of time and effort. Manual input errors and oversights are also common, making it difficult to maintain the accuracy of accounting work. There is a need for a system that can solve these problems and improve the efficiency and accuracy of accounting work overall.

[0197] 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.

[0198] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each organization and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for scanning and uploading documents using a smartphone, and means for analyzing data using natural language processing technology and automatically extracting information. This enables efficient and accurate processing of many accounting documents at a logistics center, improving the efficiency and accuracy of the entire accounting operation.

[0199] "Documents" refer to paper or electronic documents such as contracts, purchase orders, invoices, and delivery notes that are handled in business activities.

[0200] "Means of receiving" refers to the process or equipment that transfers the document file uploaded by the user to the server and stores it.

[0201] "Optical character recognition technology" is a technology that extracts character information from scanned or photographed image data.

[0202] "Text information" refers to text information that has been converted into digital data from the contents of scanned or photographed documents.

[0203] "Analysis" is the process of extracting necessary data based on the extracted text information and automatically determining accounting standards and tax issues.

[0204] "Accounting standards" are the rules and methods that companies must follow when preparing financial statements.

[0205] "Tax judgment" is the process of making automated judgments based on rules and regulations regarding the calculation and application of taxes.

[0206] An "account item" is a classification item used to record a company's transactions.

[0207] "Means of suggestion" refers to the process by which the server selects appropriate account items and displays them to the user.

[0208] "Means for presenting to the user and for the user to confirm and modify" is the process of providing an interface for the user to view the proposed accounts and approve or modify them.

[0209] "Related Documents" refers to other contracts, invoices, etc. relating to the same transaction.

[0210] "Matching" is the process of checking whether information about the same transaction matches across different documents.

[0211] "Transaction information" refers to detailed data about a transaction, such as the date, amount, and counterparty.

[0212] "External accounting systems" refers to third-party accounting software or ERP systems used by a company.

[0213] The "transmission result" indicates whether the transaction information was successfully transmitted to the external accounting system.

[0214] A "smartphone" is a mobile device with advanced information processing capabilities and communication functions.

[0215] "Scanning" is the process of converting a paper document into digital image data.

[0216] "Uploading" is the process of transferring data stored on a local device to a remote system, such as a server.

[0217] "Natural language processing technology" refers to artificial intelligence technology for understanding and analyzing human language.

[0218] "Means for analyzing data and automatically extracting information" is the process of using natural language processing techniques to identify and extract important data from textual information.

[0219] The system of the present invention automatically processes accounting documents and suggests appropriate account items. This system is intended for use in logistics centers and pursues efficiency and accuracy using smartphones. The following describes the operation of the entire system and specific program processing.

[0220] System Operation Overview

[0221] 1. Upload your documents

[0222] Users can use their smartphone's camera to scan delivery notes and invoices and upload the image data to the system.

[0223] 2. Document sorting and OCR processing

[0224] The server receives the image files uploaded by the user and temporarily stores them.

[0225] The server uses optical character recognition technology (OCR) to extract text information from the image.

[0226] 3. Information analysis and extraction

[0227] The server analyzes the extracted text information and automatically extracts important information such as the transaction number, date, amount, and counterparty using natural language processing technology.

[0228] 4. Clarifying accounting and tax issues

[0229] The server makes multiple accounting and tax decisions, automatically checking, for example, whether consumption tax applies, whether payment is made in advance or later, and the payment due date.

[0230] 5. Account suggestion

[0231] The server refers to the chart of accounts set for each user and suggests appropriate accounts based on the extracted information.

[0232] The user reviews the proposed accounts and, if necessary, modifies and approves them.

[0233] 6. Document verification and entry

[0234] The server matches the relevant documents and automatically populates the transaction information.

[0235] 7. Send to accounting system

[0236] The server transmits the consolidated transaction information in a consistent manner to an external accounting system.

[0237] The server notifies the user of the transmission result.

[0238] Hardware and software used

[0239] Hardware: Smartphone (camera function), server

[0240] software:

[0241] OCR processing is performed using OpenCV and pytesseract.

[0242] Perform natural language processing using the Hugging Face Transformers library.

[0243] Build programs using Python.

[0244] Examples of concrete examples and prompts

[0245] Example 1:

[0246] If a distribution center manager wants to process multiple invoices in bulk:

[0247] Prompt: "Invoice scanned. Please analyze the data and suggest the appropriate accounting treatment."

[0248] Example 2:

[0249] At the end of the month, the accountant uploads the invoices and the accounting code is automatically suggested:

[0250] Prompt: "I uploaded an invoice. Please suggest a consumables account and confirm the payment due date."

[0251] In this way, the system of the present invention aims to improve the efficiency and accuracy of accounting operations at logistics centers.

[0252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0253] Step 1:

[0254] Users scan accounting documents such as delivery notes and invoices using their smartphone cameras and upload them to the system. The input is the scanned image file, and the output is the image data transferred to the system.

[0255] Step 2:

[0256] The server receives image files uploaded by users and temporarily stores them in storage. The input is the uploaded image file, and the output is the stored image data.

[0257] Step 3:

[0258] The server extracts text information from images using optical character recognition (OCR). Specifically, the server uses OpenCV and pytesseract to generate text data from saved image files. The input is the saved image data, and the output is the extracted text data.

[0259] Step 4:

[0260] The server analyzes the extracted text and automatically extracts important information such as transaction number, date, amount, and counterparty using natural language processing (NLP). Specifically, it uses the Hugging Face Transformers library to identify the necessary data. The input is the text data extracted by OCR, and the output is the analyzed transaction information.

[0261] Step 5:

[0262] The server makes multiple accounting and tax decisions. It automatically determines whether consumption tax applies, whether payment is made in advance or later, and the payment due date. The input is analyzed transaction information, and the output is the results of accounting processing and tax decisions.

[0263] Step 6:

[0264] The server references the chart of accounts configured for each user and suggests appropriate accounts based on the extracted information. The input is the results of accounting and tax decisions, and the output is the suggested accounts.

[0265] Step 7:

[0266] The user reviews the proposed accounts and modifies or approves them as necessary. The input is the proposed accounts and the output is the modified or approved accounts.

[0267] Step 8:

[0268] The server automatically inputs transaction information by matching it with related documents. The input is the corrected or approved account and related document data, and the output is the consolidated transaction information.

[0269] Step 9:

[0270] The server sends the consolidated transaction information to an external accounting system. Specifically, it uses APIs to link data to other accounting software or ERP systems. The input is the consolidated transaction information, and the output is the transmission result to the external system.

[0271] Step 10:

[0272] The server notifies the user of the results of transmission to the external accounting system. The input is the transmission result, and the output is a notification message to the user.

[0273] In this way, the system of the present invention realizes automatic processing of accounting documents at a logistics center through each processing step.

[0274] 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.

[0275] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, sorts out accounting and tax issues, and proposes appropriate account headings. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the operating experience is improved. Below, the operation of the entire system and specific program processing are explained in natural language.

[0276] System Operation Overview

[0277] 1. Upload your documents

[0278] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[0279] 2. Document sorting and OCR processing

[0280] The server receives documents uploaded by users and stores them in temporary storage.

[0281] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[0282] The server sends the identified documents to an AI-OCR engine to extract the text information.

[0283] 3. Information analysis and extraction

[0284] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[0285] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[0286] 4. Clarifying accounting and tax issues

[0287] The server makes multiple accounting and tax decisions based on the stored data.

[0288] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[0289] 5. Account suggestion

[0290] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0291] The server displays the proposed account items on the user's operation screen.

[0292] The user can review the proposed accounts and approve or modify them as needed.

[0293] 6. Document verification and entry

[0294] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[0295] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[0296] 7. Send to accounting system

[0297] The server transmits the final transaction information in a consistent state to the external accounting system.

[0298] The server checks whether the transmission was successful and notifies the user of the result.

[0299] 8. How the Emotion Engine Works

[0300] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[0301] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[0302] If the user is in a high stress state, the server will make suggestions to simplify and automate the operation procedure.

[0303] Specific examples

[0304] Contract processing example

[0305] 1. The user scans the contract and saves it in PDF format on their device.

[0306] 2. The user opens the system's upload function and uploads the saved contract to the server.

[0307] 3. The server receives the uploaded contract and stores it in temporary storage.

[0308] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[0309] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[0310] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[0311] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[0312] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[0313] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[0314] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0315] 11. The server checks whether the transmission was successful and notifies the user of the result.

[0316] 12. The server uses an emotion engine to monitor the user's emotional state and simplifies the interface if stress levels are high.

[0317] In this way, the system of the present invention not only significantly improves the efficiency of accounting work and enables accurate accounting processing, but also improves the user's operating experience through its emotion engine.

[0318] The processing flow will be explained below.

[0319] Step 1:

[0320] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[0321] Step 2:

[0322] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[0323] Step 3:

[0324] The server receives the uploaded documents and stores them in temporary storage.

[0325] Step 4:

[0326] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[0327] Step 5:

[0328] The server sends the identified documents to the AI-OCR engine to extract the text information.

[0329] Step 6:

[0330] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[0331] Step 7:

[0332] The server uses existing pattern matching algorithms and natural language processing technology to accurately extract the necessary information and store it in a database.

[0333] Step 8:

[0334] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[0335] Step 9:

[0336] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0337] Step 10:

[0338] The server displays the selected account items on the user's operation screen.

[0339] Step 11:

[0340] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[0341] Step 12:

[0342] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[0343] Step 13:

[0344] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[0345] Step 14:

[0346] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0347] Step 15:

[0348] The server checks whether the transmission was successful and notifies the user of the result.

[0349] Step 16:

[0350] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[0351] Step 17:

[0352] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[0353] Step 18:

[0354] If the user is in a high stress state, the server will suggest ways to simplify and, if necessary, automate the operation procedure.

[0355] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders, and also recognizes the user's emotional state to improve the operating experience.

[0356] Example 2

[0357] Next, a description will be given of 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."

[0358] Processing accounting documents is often manual, time-consuming, and prone to errors. Furthermore, highly specialized knowledge is required to make decisions in accordance with specific accounting standards and tax issues, making it difficult to process documents efficiently and accurately. Furthermore, there is a lack of mechanisms to improve the user experience.

[0359] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standards and tax decisions, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to the user and allowing the user to confirm and correct them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, and means for recognizing the user's emotional state and dynamically adjusting the interface. This not only enables efficient and accurate processing of accounting documents, but also improves the user's operating experience.

[0360] The "means for receiving documents" is a function in which the server receives documents uploaded by the user using the terminal and stores them in temporary storage.

[0361] "Optical character recognition technology" is a technology that extracts character information from documents as digital data, a process that converts handwritten or printed text into a machine-readable format.

[0362] "Means for analyzing extracted information" refers to a function for identifying and organizing important information such as contract number, contract date, amount, and business partner based on text data extracted using optical character recognition technology.

[0363] "Means for making accounting standards and tax decisions" is a function that automatically makes appropriate decisions based on extracted information in accordance with multiple accounting standards and tax issues.

[0364] "Means for referencing and proposing account items set for each company" is a function that selects the most appropriate account items from each company's specific account item chart and proposes them to the user.

[0365] "Means for presenting proposed account items to the user and confirming / modifying them" refers to an interface that allows the server to display the proposed account items to the user, and for the user to confirm them and modify them as necessary.

[0366] The "means for automatically inputting transaction information by checking against related documents" is a function for automatically inputting accurate transaction information by checking against related documents in the database.

[0367] The "means for transmitting integrated transaction information to an external accounting system" is a function for converting final transaction information into an appropriate format and transmitting the data to an external accounting system.

[0368] The "means for notifying the user of the transmission result" is a function in which the server checks whether the data transmission to the external accounting system was successful and notifies the user of the result.

[0369] "Means for recognizing the user's emotional state and dynamically adjusting the interface" is a function that uses an emotion engine to analyze the user's emotional state and dynamically change the operation interface and feedback based on that.

[0370] MODE FOR CARRYING OUT THE INVENTION

[0371] The system of the present invention automatically processes accounting documents (contracts, purchase orders, invoices, etc.), makes accounting and tax decisions, and proposes appropriate account headings for the company. It also combines an emotion engine that recognizes the user's emotional state to improve the user experience.

[0372] System configuration

[0373] This system is configured using the following hardware and software.

[0374] 1. Server: The central unit that performs the main data processing. It is equipped with a high-performance processor and a large memory capacity. For data storage, it uses a database management system (e.g., MySQL, PostgreSQL).

[0375] 2. Terminal: A device operated by a user, such as a PC or smartphone. A browser or dedicated application is installed on the terminal.

[0376] 3. AI-OCR engine: A system that provides optical character recognition technology for extracting text information. A specific example of its use is the Google Cloud Vision API.

[0377] 4. NLP engine: An engine that uses natural language processing technology to improve the accuracy of extracted information. For example, spaCy is an example of this.

[0378] 5. Emotion Engine: An engine that recognizes user emotions and improves the operating experience, utilizing the Microsoft Emotion API.

[0379] System Operation Overview

[0380] The operation of the entire system will now be described in detail.

[0381] 1. Upload your documents

[0382] Users scan or photograph accounting documents and save them on their PC, smartphone, or other device, and then upload the documents to the server via the system's web interface or a dedicated app.

[0383] The terminal transmits a request to upload the selected file to the server.

[0384] 2. Receiving and sorting documents

[0385] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[0386] The server analyzes the stored files and automatically identifies their type, such as contract, invoice, purchase order, etc.

[0387] 3. Optical Character Recognition and Information Extraction

[0388] The server uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text information from the file.

[0389] The server receives the OCR processing results and temporarily stores the text data.

[0390] 4. Analysis of Information

[0391] The server analyzes the text data extracted from the OCR and identifies important information such as the contract number, contract date, amount, and business partner.

[0392] The server uses natural language processing (NLP) technology (e.g., spaCy) to accurately extract the required information and store it in the system's database.

[0393] 5. Clarifying accounting and tax issues

[0394] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[0395] 6. Accounting Proposal

[0396] The server looks up each company's specific chart of accounts and runs an algorithm to select the appropriate accounts.

[0397] The server displays the proposed account items on the user's operation screen so that the user can confirm and modify them.

[0398] 7. Document verification and entry

[0399] The server searches for relevant documents in the database, collates the information, and automatically enters the necessary transaction information (such as account, amount, and tax information).

[0400] 8. Send to accounting system

[0401] The server converts the final transaction information into the appropriate format and sends it to an external accounting system (e.g., SAP, QuickBooks).

[0402] The server checks whether the transmission was successful and notifies the user of the result.

[0403] 9. Emotion Engine Operation

[0404] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voices as the user operates the interface and recognize the user's emotional state.

[0405] The server dynamically adjusts the interface and feedback based on the user's emotional state. If the user is in a high stress state, the server suggests simplifying and automating the operation procedure.

[0406] Specific examples

[0407] Contract processing example

[0408] 1. The user scans the contract and saves it in PDF format on their device.

[0409] 2. The user activates the system's upload function and uploads the saved contract to the server.

[0410] 3. The device selects a file and sends an upload request to the server.

[0411] 4. The server receives the uploaded contract and stores it in temporary storage.

[0412] 5. The server automatically identifies the file as a contract and extracts the text data using an AI-OCR engine.

[0413] 6. The server analyzes the extracted data (contract number, contract date, amount, business partner, etc.) and stores it in a database.

[0414] 7. The server automatically determines whether consumption tax applies and the payment due date based on the stored data.

[0415] 8. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[0416] 9. The user reviews the proposed accounts and modifies and approves them as necessary.

[0417] 10. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[0418] 11. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0419] 12. The server confirms the transmission was successful and notifies the user of the result.

[0420] 13. The server uses an emotion engine to analyze the user's emotional state and simplifies the interface if the stress level is high.

[0421] Example of input prompt for generative AI model

[0422] Please explain in natural language how the following system works: The system works as follows:

[0423] 1. The user uploads the accounting document to the terminal.

[0424] 2. The server receives the uploaded document, automatically identifies it, performs OCR processing, and extracts the text information.

[0425] 3. The server analyzes the extracted information and stores important information such as the contract number, contract date, amount, and business partner in a database.

[0426] 4. The server organizes accounting standards and tax issues based on the stored information and suggests appropriate account items.

[0427] 5. The user reviews the proposed accounts, makes any necessary corrections, and approves them.

[0428] 6. The server sends the information to the accounting system, confirms success, and notifies the user.

[0429] 7. The server analyzes the user's emotions using an emotion engine to optimize the operating experience.

[0430] Based on this, please explain the overall operation of the system and the specific program processing.

[0431] The above is a detailed description of the "Mode for Carrying Out the Invention."

[0432] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0433] Step 1:

[0434] Document upload

[0435] Users scan or photograph accounting documents, save them as PDF or image files on their devices, and then upload the documents to the server via the system's web interface or a dedicated app.

[0436] Input: Accounting document file (PDF or image file)

[0437] Output: Upload request to server

[0438] Specific operation: The user opens the file selection dialog, selects an accounting document file, and presses the "Upload" button.

[0439] Step 2:

[0440] Receiving and temporarily storing documents

[0441] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[0442] Input: Uploaded accounting document file

[0443] Output: Files and their metadata stored in temporary storage

[0444] Specific operation: The server saves the received file in storage and records the metadata in the database.

[0445] Step 3:

[0446] Document sorting

[0447] The server analyzes the stored files and automatically identifies the type of document, such as a contract, invoice, or purchase order.

[0448] Input: A file saved in temporary storage

[0449] Output: Identified document type metadata

[0450] How it works: The server checks the file contents and determines the document type based on a pre-trained model.

[0451] Step 4:

[0452] Optical character recognition (OCR)

[0453] The server extracts text information from the file using an AI-OCR engine (e.g., Google Cloud Vision API).

[0454] Input: Identified accounting document file

[0455] Output: Extracted character information (text data)

[0456] Specific operation: The server sends the file to the AI-OCR engine and obtains the character information.

[0457] Step 5:

[0458] Analysis of information

[0459] The server analyzes the text data extracted from the OCR and extracts important information such as the contract number, contract date, amount, and business partner.

[0460] Input: Text data extracted from OCR

[0461] Output: Extracted important information (contract number, contract date, amount, business partner, etc.)

[0462] Specific operation: The server analyzes the text data using natural language processing (NLP) technology (e.g., spaCy) and extracts the necessary information.

[0463] Step 6:

[0464] Clarifying accounting and tax issues

[0465] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[0466] Input: Sensitive information stored in the database

[0467] Output: Organized accounting and tax information

[0468] Specific operation: The server automatically determines whether consumption tax applies, the payment due date, etc. in accordance with accounting standards and tax regulations.

[0469] Step 7:

[0470] Account suggestion

[0471] The server refers to the chart of accounts set for each company and selects the most appropriate account.

[0472] Input: Organized accounting and tax information

[0473] Output: Proposed accounts

[0474] How it works: The server runs an algorithm to suggest appropriate accounts from each company's chart of accounts.

[0475] Step 8:

[0476] Account suggestion and adjustment

[0477] The server displays the proposed account items on the user's operation screen.

[0478] The user reviews the proposed accounts and makes any necessary corrections.

[0479] Input: Proposed Account

[0480] Output: Accounts confirmed and modified by the user

[0481] Specific behavior: The user reviews the proposed accounts on the screen, makes any necessary corrections, and finally approves them.

[0482] Step 9:

[0483] Document verification and entry

[0484] The server retrieves relevant documents from a database and collates the information.

[0485] The server automatically enters the necessary information (subject, amount, tax information, etc.) based on the matching results.

[0486] Input: Related documents and accounts modified and approved by the user

[0487] Output: Auto-filled transaction information

[0488] How it works: The server searches for relevant documents in a database, collates the information, and automatically fills in the necessary transaction information.

[0489] Step 10:

[0490] Send to accounting system

[0491] The server converts the final transaction information into the appropriate format while maintaining consistency and transmits it to the external accounting system.

[0492] The server checks whether the transmission was successful and notifies the user of the result.

[0493] Input: Auto-filled transaction information

[0494] Output: Transaction information sent to an external accounting system and notification of the sending result

[0495] Specific operations: The server converts the transaction information into an appropriate format, sends the data to the external accounting system, confirms the success of the transmission, and notifies the user.

[0496] Step 11:

[0497] Emotion Engine Operation

[0498] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voice as the user interacts with the interface and recognize the user's emotional state.

[0499] The server dynamically adjusts the interface and feedback based on the perceived emotional state.

[0500] Input: User's facial expressions and voice data

[0501] Output: Dynamically adjusted interface and feedback

[0502] Specific operation: The server uses the emotion engine to monitor the user's emotional state and adjust the interface and feedback.

[0503] The above is the flow of processing of the program of this system.

[0504] (Application example 2)

[0505] Next, a description will be given of Application 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."

[0506] Modern accounting work involves manual document processing and determining accounting standards, which is extremely tedious and prone to human error. Furthermore, the mental burden of performing the work is significant, leading to stress. Therefore, along with streamlining accounting work, there is a demand for improved user interfaces to enhance the user experience.

[0507] 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 means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standards and tax decisions, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to the user and allowing the user to confirm or correct them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, and means for dynamically adjusting the operating experience using an emotion engine that recognizes the user's emotions. This enables more efficient accounting work and reduces user stress.

[0508] Definition of Terms

[0509] "Document" means accounting documents (e.g., contracts, purchase orders, invoices, etc.), whether in handwritten or printed form.

[0510] "Means for receiving" refers to the technology or process by which the server receives input from the user and saves the data in storage.

[0511] "Optical character recognition technology" is a technology that extracts character information from an image and converts it into text format.

[0512] The "means of extraction" is a process for extracting textual information from a document using optical character recognition technology.

[0513] "Means for analyzing and making accounting and tax judgments" refers to algorithms and logic for automatically determining applicable accounting and tax standards based on the extracted information.

[0514] The "means for proposing account items" is a process for selecting appropriate account categories based on the accounting standards of each company and presenting them to the user.

[0515] "Means for users to confirm and correct" refers to an interface that allows users to visually check the proposed account items and correct them if necessary.

[0516] "Means for matching and automatically entering transaction information" means a technology or process that matches related documents and automatically enters matching information.

[0517] The "means for transmitting to the accounting system" refers to a communication technology for transferring consistent transaction information to an external accounting system.

[0518] "Means for notifying transmission results" refers to the technology or process that notifies the user whether data transmission was successful.

[0519] An "emotion engine" is an algorithm or model for analyzing and recognizing a user's emotional state from their facial expressions or voice.

[0520] "Dynamic adjustment means" refers to a process of adaptively changing the operating procedures and display content of the user interface based on the analysis results of the emotion engine.

[0521] MODE FOR CARRYING OUT THE INVENTION

[0522] The present invention provides a system that automatically processes accounting documents, makes accounting and tax decisions, and proposes optimal account items. It also incorporates an emotion engine that recognizes user emotions to improve the user experience.

[0523] System configuration

[0524] 1. Receiving documents: The user scans or photographs accounting documents and uploads them to the system using a device (smartphone or PC). The server receives them and stores them in temporary storage.

[0525] 2. OCR Processing: The server uses optical character recognition technology (e.g., Tesseract OCR) to extract text information from the uploaded document.

[0526] 3. Information analysis: Based on the extracted text information, natural language processing technology is used to analyze and extract important data such as the contract number, contract date, amount, and counterparty, using existing pattern matching algorithms and AI technology.

[0527] 4. Accounting and tax decisions: The server automatically determines accounting standards and taxation based on the analyzed data. For example, it checks whether consumption tax applies and the payment due date.

[0528] 5. Account suggestion: The system refers to the chart of accounts set for each company and suggests appropriate accounts to the user. The user can review the suggestions and modify or approve them as necessary.

[0529] 6. Automatic entry of transaction information: The server checks the transaction information against other related documents and automatically enters it.

[0530] 7. Send to external accounting system: Integrate the final transaction information to the external accounting system and send the data. Check whether the sending was successful and notify the user of the result.

[0531] 8. Emotion Recognition: An emotion engine analyzes the user's facial expressions and voice to recognize their emotional state. Dynamically adjust the interface if stress levels are high.

[0532] Hardware and software used

[0533] Hardware: Smartphones, PCs, servers

[0534] software:

[0535] OpenCV: Used for image processing

[0536] Tesseract OCR: Character recognition

[0537] sklearn:Data standardization

[0538] keras: A neural network model for emotion recognition

[0539] Generative AI models and prompts: Natural language processing techniques

[0540] Unique financial information identification module: financial data extraction

[0541] Unique database module: data storage and collation

[0542] Specific examples

[0543] 1. Prompt: Please enter the path to the accounting document.

[0544] 2. Input example: C: / documents / invoice_2023.pdf

[0545] 3. Example output:

[0546] "Proposed Accounts: 'Purchases', 'Sales'"

[0547] "Users are frustrated. We're simplifying the process."

[0548] In this way, the present invention realizes efficient accounting work, reduces user stress, and provides a better operating experience.

[0549] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0550] Program processing flow

[0551] Step 1:

[0552] A user scans or photographs accounting documents (e.g., contracts, purchase orders, invoices, etc.) using a smartphone or PC, and uploads the image file to the system. At this time, the input for uploading is the path to the image file. The server receives the image file and stores it in temporary storage.

[0553] Step 2:

[0554] The server reads the saved image file and extracts the text information using optical character recognition technology (Tesseract OCR). The input is the image file, and the output is the text information in text format.

[0555] Step 3:

[0556] The server analyzes the extracted text information using natural language processing technology (generative AI model and prompt text) to extract important data such as the contract number, contract date, amount, counterparty, etc. The input is text information in text format, and the output is the extracted data (e.g., contract number, contract date, amount, counterparty, etc.).

[0557] Step 4:

[0558] The server makes accounting standards and tax decisions based on the extracted data. During this process, it automatically checks whether consumption tax applies, the payment due date, etc. The input is the extracted data, and the output is the accounting standards and tax decisions.

[0559] Step 5:

[0560] The server refers to the chart of accounts set for each company and suggests appropriate accounts to the user. At this time, a comparison is made with the chart of accounts database. The input is the accounting standards and the results of tax decisions, and the output is the suggested accounts.

[0561] Step 6:

[0562] The user reviews the proposed accounts and modifies and approves them as necessary. The input is the proposed accounts and the output is the accounts modified and approved by the user.

[0563] Step 7:

[0564] The server automatically inputs transaction information based on the account item approved by the user, checking it against other related documents (e.g., invoices, receipts, etc.) The input is the approved account item and related documents, and the output is the automatically input transaction information.

[0565] Step 8:

[0566] The server sends the final transaction information to the external accounting system. It checks whether the transmission was successful and notifies the user of the result. The input is the automatically entered transaction information, and the output is the transmission result to the accounting system.

[0567] Step 9:

[0568] While the user is operating the system, the server uses an emotion engine to analyze facial expressions and voice to recognize the user's emotional state. If stress levels are high, the server dynamically adjusts the interface and suggests ways to simplify the operation procedure. The input is the user's facial and voice data, and the output is the user's emotional state and the interface adjustment results.

[0569] 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.

[0570] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[0571] 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.

[0572] [Second embodiment]

[0573] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0574] 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.

[0575] 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).

[0576] 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.

[0577] 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.

[0578] 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).

[0579] 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.

[0580] 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.

[0581] 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.

[0582] 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.

[0583] 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.

[0584] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0585] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[0586] System Operation Overview

[0587] 1. Upload your documents

[0588] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[0589] 2. Document sorting and OCR processing

[0590] The server receives documents uploaded by users and stores them in temporary storage.

[0591] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[0592] The server sends the identified documents to an AI-OCR engine to extract the text information.

[0593] 3. Information analysis and extraction

[0594] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[0595] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[0596] 4. Clarifying accounting and tax issues

[0597] The server makes multiple accounting and tax decisions based on the stored data.

[0598] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[0599] 5. Account suggestion

[0600] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0601] The server displays the proposed account items on the user's operation screen.

[0602] The user can review the proposed accounts and approve or modify them as needed.

[0603] 6. Document verification and entry

[0604] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[0605] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[0606] 7. Send to accounting system

[0607] The server transmits the final transaction information in a consistent state to the external accounting system.

[0608] The server checks whether the transmission was successful and notifies the user of the result.

[0609] Specific examples

[0610] Contract processing example

[0611] 1. The user scans the contract and saves it in PDF format on their device.

[0612] 2. The user opens the system's upload function and uploads the saved contract to the server.

[0613] 3. The server receives the uploaded contract and stores it in temporary storage.

[0614] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[0615] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[0616] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[0617] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[0618] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[0619] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[0620] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0621] 11. The server checks whether the transmission was successful and notifies the user of the result.

[0622] In this way, the system of the present invention significantly improves the efficiency of accounting work and enables accurate accounting processing.

[0623] The processing flow will be explained below.

[0624] Step 1:

[0625] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[0626] Step 2:

[0627] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[0628] Step 3:

[0629] The server receives the uploaded documents and stores them in temporary storage.

[0630] Step 4:

[0631] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[0632] Step 5:

[0633] The server sends the identified documents to the AI-OCR engine to extract the text information.

[0634] Step 6:

[0635] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[0636] Step 7:

[0637] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[0638] Step 8:

[0639] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[0640] Step 9:

[0641] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0642] Step 10:

[0643] The server displays the selected account items on the user's operation screen.

[0644] Step 11:

[0645] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[0646] Step 12:

[0647] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[0648] Step 13:

[0649] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[0650] Step 14:

[0651] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0652] Step 15:

[0653] The server checks whether the transmission was successful and notifies the user of the result.

[0654] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders.

[0655] Example 1

[0656] Next, a description will be given of 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."

[0657] In accounting work, it is common to manually process documents such as contracts and purchase orders, which requires a great deal of time and effort. Manual data entry is prone to human error, which can lead to inaccurate accounting and tax decisions. Furthermore, efficient processing of vast amounts of accounting documents and accurate accounting procedures requires advanced technology, which places a heavy burden on many companies.

[0658] 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.

[0659] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for temporarily storing uploaded documents, means for transmitting to a corresponding optical character recognition engine based on the automatically identified documents, means for analyzing and parsing important information using natural language processing technology, and means for referencing a relational database that stores analyzed information each time. This enables automatic processing of accounting documents, thereby improving processing efficiency and accuracy.

[0660] The "means for receiving documents" is a function for receiving accounting documents uploaded by users and temporarily storing them.

[0661] "Optical character recognition technology" is a technology that automatically extracts text information from documents stored in digital formats such as images and PDFs.

[0662] The "means for analyzing extracted information" is a function for analyzing extracted character information using optical character recognition technology and extracting necessary data.

[0663] "Means for making multiple accounting standards and tax decisions" refers to a function that automatically makes various accounting standards and tax decisions based on extracted and analyzed data.

[0664] "Means for referencing account items set for each company" refers to a function for referencing an account item chart customized for each company and selecting appropriate account items.

[0665] The "means for proposing appropriate account items" is a function for proposing the most appropriate account items based on the analyzed information.

[0666] The "means for presenting the proposed account items to the user" is a function for displaying the selected account items to the user and enabling confirmation and correction.

[0667] "Means for user confirmation and correction" is a function that allows users to check the proposed account items and correct them if necessary.

[0668] "Means for comparing with related documents and automatically inputting transaction information" is a function for comparing existing related documents with uploaded documents and automatically inputting transaction information.

[0669] The "means for transmitting integrated transaction information to an external accounting system" is a function for transmitting the final integrated transaction information in a predetermined format to an external accounting system.

[0670] The "means for notifying the user of the transmission result" is a function for checking whether the data transmission to the external accounting system was successful and notifying the user of the result.

[0671] The "means for temporarily storing uploaded documents" is a function for temporarily storing documents uploaded by users in cloud storage or the like.

[0672] The "means for transmitting to a corresponding optical character recognition engine based on the automatically identified document" is a function for transmitting data to an appropriate optical character recognition engine depending on the type of automatically identified document.

[0673] "Means for analyzing and interpreting important information using natural language processing technology" refers to a function that uses natural language processing technology to accurately analyze important information from extracted text data.

[0674] "Means for referencing the relational database that stores analyzed information each time" refers to a function for referencing the relational database that stores analyzed information each time and retrieving the necessary data at the appropriate time.

[0675] The system of the present invention automatically processes accounting documents, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[0676] System Overview

[0677] This system is primarily composed of a server, user devices, and several software components. The server receives accounting documents, stores them, processes them with OCR, analyzes the information, proposes account items, collates documents, and sends the data to the accounting system. The user device scans accounting documents and uploads them to the system. The specific usage of each piece of hardware and software is explained below.

[0678] Document upload

[0679] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). Then, they open the system interface, select the digitized document file (PDF or image format), and click the upload button. The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3).

[0680] Document sorting and OCR processing

[0681] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). Based on the identification results, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The extracted text data is stored in a temporary database (e.g., MongoDB).

[0682] Information analysis and extraction

[0683] The server extracts the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The extracted important information is stored in a relational database (e.g., MySQL).

[0684] Clarifying accounting and tax issues

[0685] The server uses the stored data to make accounting and tax decisions, such as whether consumption tax applies, whether payment is made in advance or later, and whether payment is due, using a specific software library (e.g., PyDSTool).

[0686] Account suggestion

[0687] The server references a custom chart of accounts (e.g., a QuickBooks account list) configured for each company. Based on the analyzed information, it recommends appropriate accounts and displays them on the user's screen. The user can review the recommended accounts and modify or approve them as necessary.

[0688] Document verification and entry

[0689] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered to complete the required information.

[0690] Send to accounting system

[0691] The server finally converts the organized transaction information into the format of the ERP system (e.g., SAP ERP), sends the converted data to the external accounting system, checks the transmission results, and finally notifies the user of the transmission results.

[0692] Specific examples

[0693] Contract processing example

[0694] 1. The user scans the contract and saves it on their device.

[0695] 2. The user opens the system interface and uploads the contract file.

[0696] 3. The server receives the file and temporarily stores it in cloud storage.

[0697] 4. The server automatically identifies the file type as a contract using the cloud service API.

[0698] 5. The server sends the file to the OCR engine and extracts the character data.

[0699] 6. The server stores the extracted data in a temporary database.

[0700] 7. The server analyzes the data using natural language processing libraries and stores important information in a relational database.

[0701] 8. The server organizes accounting and tax standards and automatically determines tax issues.

[0702] 9. The server consults the chart of accounts and recommends the most appropriate accounts to the user.

[0703] 10. The user reviews the proposed accounts and makes any necessary modifications.

[0704] 11. The server compares the contract with other related documents and automatically fills in the required information.

[0705] 12. The server converts the data into ERP format and sends it to the accounting system.

[0706] 13. The server checks the transmission result and notifies the user.

[0707] Prompt Sentence Examples

[0708] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[0709] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[0710] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0711] Program processing steps

[0712] Step 1:

[0713] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). They select the digitized file (PDF or image format) in the system interface and click the upload button. The input is the physical file of the accounting document, and the output is the digital file saved on their device.

[0714] Step 2:

[0715] The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3). The input is the uploaded digital file, and the output is the file stored in the cloud storage.

[0716] Step 3:

[0717] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). The input is the file stored in cloud storage, and the output is the document type identification result. Based on the identification result, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The input is the document type and file, and the output is the extracted text data.

[0718] Step 4:

[0719] The server stores the character data obtained by OCR processing in a temporary database (e.g., MongoDB). The input is the character data extracted by OCR processing, and the output is the data stored in the temporary database.

[0720] Step 5:

[0721] The server takes the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The input is the stored text data, and the output is the analyzed important information. The extracted important information is stored in a relational database (e.g., MySQL). Specifically, the server uses SpaCy to tokenize the text data and applies a specific pattern matching algorithm.

[0722] Step 6:

[0723] The server uses the stored data to make accounting and tax decisions. For example, it uses a specific software library (e.g., PyDSTool) to perform automated decisions such as whether consumption tax applies or confirming payment due dates. The input is data stored in a relational database, and the output is the accounting and tax decisions.

[0724] Step 7:

[0725] The server references a custom chart of accounts configured for each company (e.g., a custom list of accounts in accounting software). The input is the parsed information and the chart of accounts, and the output is the recommendation of the best accounts. Specifically, the server reads the chart of accounts from the database and runs an algorithm to select the appropriate accounts.

[0726] Step 8:

[0727] The server displays the recommended accounts on the user's screen, and the user can review, modify, and approve them as necessary. The input is the recommended accounts, and the output is the accounts confirmed by the user.

[0728] Step 9:

[0729] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered and necessary information is completed. The input is the related documents and analyzed information, and the output is the completed transaction information.

[0730] Step 10:

[0731] The server finally converts the organized transaction information into the format of an ERP system (e.g., enterprise resource planning software). It then sends the converted data to an external accounting system and checks the transmission result. The input is the completed transaction information, and the output is the data converted into the ERP format and the transmission result. Finally, it notifies the user of the transmission result.

[0732] Prompt Sentence Examples

[0733] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[0734] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[0735] (Application example 1)

[0736] Next, a description will be given of Application 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."

[0737] Modern logistics centers handle a large number of delivery notes and invoices every day, and manually processing these documents requires a huge amount of time and effort. Manual input errors and oversights are also common, making it difficult to maintain the accuracy of accounting work. There is a need for a system that can solve these problems and improve the efficiency and accuracy of accounting work overall.

[0738] 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.

[0739] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each organization and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for scanning and uploading documents using a smartphone, and means for analyzing data using natural language processing technology and automatically extracting information. This enables efficient and accurate processing of many accounting documents at a logistics center, improving the efficiency and accuracy of the entire accounting operation.

[0740] "Documents" refer to paper or electronic documents such as contracts, purchase orders, invoices, and delivery notes that are handled in business activities.

[0741] "Means of receiving" refers to the process or equipment that transfers the document file uploaded by the user to the server and stores it.

[0742] "Optical character recognition technology" is a technology that extracts character information from scanned or photographed image data.

[0743] "Text information" refers to text information that has been converted into digital data from the contents of scanned or photographed documents.

[0744] "Analysis" is the process of extracting necessary data based on the extracted text information and automatically determining accounting standards and tax issues.

[0745] "Accounting standards" are the rules and methods that companies must follow when preparing financial statements.

[0746] "Tax judgment" is the process of making automated judgments based on rules and regulations regarding the calculation and application of taxes.

[0747] An "account item" is a classification item used to record a company's transactions.

[0748] "Means of suggestion" refers to the process by which the server selects appropriate account items and displays them to the user.

[0749] "Means for presenting to the user and for the user to confirm and modify" is the process of providing an interface for the user to view the proposed accounts and approve or modify them.

[0750] "Related Documents" refers to other contracts, invoices, etc. relating to the same transaction.

[0751] "Matching" is the process of checking whether information about the same transaction matches across different documents.

[0752] "Transaction information" refers to detailed data about a transaction, such as the date, amount, and counterparty.

[0753] "External accounting systems" refers to third-party accounting software or ERP systems used by a company.

[0754] The "transmission result" indicates whether the transaction information was successfully transmitted to the external accounting system.

[0755] A "smartphone" is a mobile device with advanced information processing capabilities and communication functions.

[0756] "Scanning" is the process of converting a paper document into digital image data.

[0757] "Uploading" is the process of transferring data stored on a local device to a remote system, such as a server.

[0758] "Natural language processing technology" refers to artificial intelligence technology for understanding and analyzing human language.

[0759] "Means for analyzing data and automatically extracting information" is the process of using natural language processing techniques to identify and extract important data from textual information.

[0760] The system of the present invention automatically processes accounting documents and suggests appropriate account items. This system is intended for use in logistics centers and pursues efficiency and accuracy using smartphones. The following describes the operation of the entire system and specific program processing.

[0761] System Operation Overview

[0762] 1. Upload your documents

[0763] Users can use their smartphone's camera to scan delivery notes and invoices and upload the image data to the system.

[0764] 2. Document sorting and OCR processing

[0765] The server receives the image files uploaded by the user and temporarily stores them.

[0766] The server uses optical character recognition technology (OCR) to extract text information from the image.

[0767] 3. Information analysis and extraction

[0768] The server analyzes the extracted text information and automatically extracts important information such as the transaction number, date, amount, and counterparty using natural language processing technology.

[0769] 4. Clarifying accounting and tax issues

[0770] The server makes multiple accounting and tax decisions, automatically checking, for example, whether consumption tax applies, whether payment is made in advance or later, and the payment due date.

[0771] 5. Account suggestion

[0772] The server refers to the chart of accounts set for each user and suggests appropriate accounts based on the extracted information.

[0773] The user reviews the proposed accounts and, if necessary, modifies and approves them.

[0774] 6. Document verification and entry

[0775] The server matches the relevant documents and automatically populates the transaction information.

[0776] 7. Send to accounting system

[0777] The server transmits the consolidated transaction information in a consistent manner to an external accounting system.

[0778] The server notifies the user of the transmission result.

[0779] Hardware and software used

[0780] Hardware: Smartphone (camera function), server

[0781] software:

[0782] OCR processing is performed using OpenCV and pytesseract.

[0783] Perform natural language processing using the Hugging Face Transformers library.

[0784] Build programs using Python.

[0785] Examples of concrete examples and prompts

[0786] Example 1:

[0787] If a distribution center manager wants to process multiple invoices in bulk:

[0788] Prompt: "Invoice scanned. Please analyze the data and suggest the appropriate accounting treatment."

[0789] Example 2:

[0790] At the end of the month, the accountant uploads the invoices and the accounting code is automatically suggested:

[0791] Prompt: "I uploaded an invoice. Please suggest a consumables account and confirm the payment due date."

[0792] In this way, the system of the present invention aims to improve the efficiency and accuracy of accounting operations at logistics centers.

[0793] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0794] Step 1:

[0795] Users scan accounting documents such as delivery notes and invoices using their smartphone cameras and upload them to the system. The input is the scanned image file, and the output is the image data transferred to the system.

[0796] Step 2:

[0797] The server receives image files uploaded by users and temporarily stores them in storage. The input is the uploaded image file, and the output is the stored image data.

[0798] Step 3:

[0799] The server extracts text information from images using optical character recognition (OCR). Specifically, the server uses OpenCV and pytesseract to generate text data from saved image files. The input is the saved image data, and the output is the extracted text data.

[0800] Step 4:

[0801] The server analyzes the extracted text and automatically extracts important information such as transaction number, date, amount, and counterparty using natural language processing (NLP). Specifically, it uses the Hugging Face Transformers library to identify the necessary data. The input is the text data extracted by OCR, and the output is the analyzed transaction information.

[0802] Step 5:

[0803] The server makes multiple accounting and tax decisions. It automatically determines whether consumption tax applies, whether payment is made in advance or later, and the payment due date. The input is analyzed transaction information, and the output is the results of accounting processing and tax decisions.

[0804] Step 6:

[0805] The server references the chart of accounts configured for each user and suggests appropriate accounts based on the extracted information. The input is the results of accounting and tax decisions, and the output is the suggested accounts.

[0806] Step 7:

[0807] The user reviews the proposed accounts and modifies or approves them as necessary. The input is the proposed accounts and the output is the modified or approved accounts.

[0808] Step 8:

[0809] The server automatically inputs transaction information by matching it with related documents. The input is the corrected or approved account and related document data, and the output is the consolidated transaction information.

[0810] Step 9:

[0811] The server sends the consolidated transaction information to an external accounting system. Specifically, it uses APIs to link data to other accounting software or ERP systems. The input is the consolidated transaction information, and the output is the transmission result to the external system.

[0812] Step 10:

[0813] The server notifies the user of the results of transmission to the external accounting system. The input is the transmission result, and the output is a notification message to the user.

[0814] In this way, the system of the present invention realizes automatic processing of accounting documents at a logistics center through each processing step.

[0815] 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.

[0816] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, sorts out accounting and tax issues, and proposes appropriate account headings. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the operating experience is improved. Below, the operation of the entire system and specific program processing are explained in natural language.

[0817] System Operation Overview

[0818] 1. Upload your documents

[0819] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[0820] 2. Document sorting and OCR processing

[0821] The server receives documents uploaded by users and stores them in temporary storage.

[0822] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[0823] The server sends the identified documents to an AI-OCR engine to extract the text information.

[0824] 3. Information analysis and extraction

[0825] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[0826] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[0827] 4. Clarifying accounting and tax issues

[0828] The server makes multiple accounting and tax decisions based on the stored data.

[0829] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[0830] 5. Account suggestion

[0831] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0832] The server displays the proposed account items on the user's operation screen.

[0833] The user can review the proposed accounts and approve or modify them as needed.

[0834] 6. Document verification and entry

[0835] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[0836] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[0837] 7. Send to accounting system

[0838] The server transmits the final transaction information in a consistent state to the external accounting system.

[0839] The server checks whether the transmission was successful and notifies the user of the result.

[0840] 8. How the Emotion Engine Works

[0841] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[0842] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[0843] If the user is in a high stress state, the server will make suggestions to simplify and automate the operation procedure.

[0844] Specific examples

[0845] Contract processing example

[0846] 1. The user scans the contract and saves it in PDF format on their device.

[0847] 2. The user opens the system's upload function and uploads the saved contract to the server.

[0848] 3. The server receives the uploaded contract and stores it in temporary storage.

[0849] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[0850] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[0851] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[0852] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[0853] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[0854] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[0855] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0856] 11. The server checks whether the transmission was successful and notifies the user of the result.

[0857] 12. The server uses an emotion engine to monitor the user's emotional state and simplifies the interface if stress levels are high.

[0858] In this way, the system of the present invention not only significantly improves the efficiency of accounting work and enables accurate accounting processing, but also improves the user's operating experience through its emotion engine.

[0859] The processing flow will be explained below.

[0860] Step 1:

[0861] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[0862] Step 2:

[0863] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[0864] Step 3:

[0865] The server receives the uploaded documents and stores them in temporary storage.

[0866] Step 4:

[0867] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[0868] Step 5:

[0869] The server sends the identified documents to the AI-OCR engine to extract the text information.

[0870] Step 6:

[0871] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[0872] Step 7:

[0873] The server uses existing pattern matching algorithms and natural language processing technology to accurately extract the necessary information and store it in a database.

[0874] Step 8:

[0875] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[0876] Step 9:

[0877] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[0878] Step 10:

[0879] The server displays the selected account items on the user's operation screen.

[0880] Step 11:

[0881] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[0882] Step 12:

[0883] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[0884] Step 13:

[0885] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[0886] Step 14:

[0887] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0888] Step 15:

[0889] The server checks whether the transmission was successful and notifies the user of the result.

[0890] Step 16:

[0891] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[0892] Step 17:

[0893] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[0894] Step 18:

[0895] If the user is in a high stress state, the server will suggest ways to simplify and, if necessary, automate the operation procedure.

[0896] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders, and also recognizes the user's emotional state to improve the operating experience.

[0897] Example 2

[0898] Next, a description will be given of 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."

[0899] Processing accounting documents is often manual, time-consuming, and prone to errors. Furthermore, highly specialized knowledge is required to make decisions in accordance with specific accounting standards and tax issues, making it difficult to process documents efficiently and accurately. Furthermore, there is a lack of mechanisms to improve the user experience.

[0900] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standards and tax decisions, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to the user and allowing the user to confirm and correct them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, and means for recognizing the user's emotional state and dynamically adjusting the interface. This not only enables efficient and accurate processing of accounting documents, but also improves the user's operating experience.

[0901] The "means for receiving documents" is a function in which the server receives documents uploaded by the user using the terminal and stores them in temporary storage.

[0902] "Optical character recognition technology" is a technology that extracts character information from documents as digital data, a process that converts handwritten or printed text into a machine-readable format.

[0903] "Means for analyzing extracted information" refers to a function for identifying and organizing important information such as contract number, contract date, amount, and business partner based on text data extracted using optical character recognition technology.

[0904] "Means for making accounting standards and tax decisions" is a function that automatically makes appropriate decisions based on extracted information in accordance with multiple accounting standards and tax issues.

[0905] "Means for referencing and proposing account items set for each company" is a function that selects the most appropriate account items from each company's specific account item chart and proposes them to the user.

[0906] "Means for presenting proposed account items to the user and confirming / modifying them" refers to an interface that allows the server to display the proposed account items to the user, and for the user to confirm them and modify them as necessary.

[0907] The "means for automatically inputting transaction information by checking against related documents" is a function for automatically inputting accurate transaction information by checking against related documents in the database.

[0908] The "means for transmitting integrated transaction information to an external accounting system" is a function for converting final transaction information into an appropriate format and transmitting the data to an external accounting system.

[0909] The "means for notifying the user of the transmission result" is a function in which the server checks whether the data transmission to the external accounting system was successful and notifies the user of the result.

[0910] "Means for recognizing the user's emotional state and dynamically adjusting the interface" is a function that uses an emotion engine to analyze the user's emotional state and dynamically change the operation interface and feedback based on that.

[0911] MODE FOR CARRYING OUT THE INVENTION

[0912] The system of the present invention automatically processes accounting documents (contracts, purchase orders, invoices, etc.), makes accounting and tax decisions, and proposes appropriate account headings for the company. It also combines an emotion engine that recognizes the user's emotional state to improve the user experience.

[0913] System configuration

[0914] This system is configured using the following hardware and software.

[0915] 1. Server: The central unit that performs the main data processing. It is equipped with a high-performance processor and a large memory capacity. For data storage, it uses a database management system (e.g., MySQL, PostgreSQL).

[0916] 2. Terminal: A device operated by a user, such as a PC or smartphone. A browser or dedicated application is installed on the terminal.

[0917] 3. AI-OCR engine: A system that provides optical character recognition technology for extracting text information. A specific example of its use is the Google Cloud Vision API.

[0918] 4. NLP engine: An engine that uses natural language processing technology to improve the accuracy of extracted information. For example, spaCy is an example of this.

[0919] 5. Emotion Engine: An engine that recognizes user emotions and improves the operating experience, utilizing the Microsoft Emotion API.

[0920] System Operation Overview

[0921] The operation of the entire system will now be described in detail.

[0922] 1. Upload your documents

[0923] Users scan or photograph accounting documents and save them on their PC, smartphone, or other device, and then upload the documents to the server via the system's web interface or a dedicated app.

[0924] The terminal transmits a request to upload the selected file to the server.

[0925] 2. Receiving and sorting documents

[0926] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[0927] The server analyzes the stored files and automatically identifies their type, such as contract, invoice, purchase order, etc.

[0928] 3. Optical Character Recognition and Information Extraction

[0929] The server uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text information from the file.

[0930] The server receives the OCR processing results and temporarily stores the text data.

[0931] 4. Analysis of Information

[0932] The server analyzes the text data extracted from the OCR and identifies important information such as the contract number, contract date, amount, and business partner.

[0933] The server uses natural language processing (NLP) technology (e.g., spaCy) to accurately extract the required information and store it in the system's database.

[0934] 5. Clarifying accounting and tax issues

[0935] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[0936] 6. Accounting Proposal

[0937] The server looks up each company's specific chart of accounts and runs an algorithm to select the appropriate accounts.

[0938] The server displays the proposed account items on the user's operation screen so that the user can confirm and modify them.

[0939] 7. Document verification and entry

[0940] The server searches for relevant documents in the database, collates the information, and automatically enters the necessary transaction information (such as account, amount, and tax information).

[0941] 8. Send to accounting system

[0942] The server converts the final transaction information into the appropriate format and sends it to an external accounting system (e.g., SAP, QuickBooks).

[0943] The server checks whether the transmission was successful and notifies the user of the result.

[0944] 9. Emotion Engine Operation

[0945] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voices as the user operates the interface and recognize the user's emotional state.

[0946] The server dynamically adjusts the interface and feedback based on the user's emotional state. If the user is in a high stress state, the server suggests simplifying and automating the operation procedure.

[0947] Specific examples

[0948] Contract processing example

[0949] 1. The user scans the contract and saves it in PDF format on their device.

[0950] 2. The user activates the system's upload function and uploads the saved contract to the server.

[0951] 3. The device selects a file and sends an upload request to the server.

[0952] 4. The server receives the uploaded contract and stores it in temporary storage.

[0953] 5. The server automatically identifies the file as a contract and extracts the text data using an AI-OCR engine.

[0954] 6. The server analyzes the extracted data (contract number, contract date, amount, business partner, etc.) and stores it in a database.

[0955] 7. The server automatically determines whether consumption tax applies and the payment due date based on the stored data.

[0956] 8. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[0957] 9. The user reviews the proposed accounts and modifies and approves them as necessary.

[0958] 10. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[0959] 11. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[0960] 12. The server confirms the transmission was successful and notifies the user of the result.

[0961] 13. The server uses an emotion engine to analyze the user's emotional state and simplifies the interface if the stress level is high.

[0962] Example of input prompt for generative AI model

[0963] Please explain in natural language how the following system works: The system works as follows:

[0964] 1. The user uploads the accounting document to the terminal.

[0965] 2. The server receives the uploaded document, automatically identifies it, performs OCR processing, and extracts the text information.

[0966] 3. The server analyzes the extracted information and stores important information such as the contract number, contract date, amount, and business partner in a database.

[0967] 4. The server organizes accounting standards and tax issues based on the stored information and suggests appropriate account items.

[0968] 5. The user reviews the proposed accounts, makes any necessary corrections, and approves them.

[0969] 6. The server sends the information to the accounting system, confirms success, and notifies the user.

[0970] 7. The server analyzes the user's emotions using an emotion engine to optimize the operating experience.

[0971] Based on this, please explain the overall operation of the system and the specific program processing.

[0972] The above is a detailed description of the "Mode for Carrying Out the Invention."

[0973] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0974] Step 1:

[0975] Document upload

[0976] Users scan or photograph accounting documents, save them as PDF or image files on their devices, and then upload the documents to the server via the system's web interface or a dedicated app.

[0977] Input: Accounting document file (PDF or image file)

[0978] Output: Upload request to server

[0979] Specific operation: The user opens the file selection dialog, selects an accounting document file, and presses the "Upload" button.

[0980] Step 2:

[0981] Receiving and temporarily storing documents

[0982] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[0983] Input: Uploaded accounting document file

[0984] Output: Files and their metadata stored in temporary storage

[0985] Specific operation: The server saves the received file in storage and records the metadata in the database.

[0986] Step 3:

[0987] Document sorting

[0988] The server analyzes the stored files and automatically identifies the type of document, such as a contract, invoice, or purchase order.

[0989] Input: A file saved in temporary storage

[0990] Output: Identified document type metadata

[0991] How it works: The server checks the file contents and determines the document type based on a pre-trained model.

[0992] Step 4:

[0993] Optical character recognition (OCR)

[0994] The server extracts text information from the file using an AI-OCR engine (e.g., Google Cloud Vision API).

[0995] Input: Identified accounting document file

[0996] Output: Extracted character information (text data)

[0997] Specific operation: The server sends the file to the AI-OCR engine and obtains the character information.

[0998] Step 5:

[0999] Analysis of information

[1000] The server analyzes the text data extracted from the OCR and extracts important information such as the contract number, contract date, amount, and business partner.

[1001] Input: Text data extracted from OCR

[1002] Output: Extracted important information (contract number, contract date, amount, business partner, etc.)

[1003] Specific operation: The server analyzes the text data using natural language processing (NLP) technology (e.g., spaCy) and extracts the necessary information.

[1004] Step 6:

[1005] Clarifying accounting and tax issues

[1006] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[1007] Input: Sensitive information stored in the database

[1008] Output: Organized accounting and tax information

[1009] Specific operation: The server automatically determines whether consumption tax applies, the payment due date, etc. in accordance with accounting standards and tax regulations.

[1010] Step 7:

[1011] Account suggestion

[1012] The server refers to the chart of accounts set for each company and selects the most appropriate account.

[1013] Input: Organized accounting and tax information

[1014] Output: Proposed accounts

[1015] How it works: The server runs an algorithm to suggest appropriate accounts from each company's chart of accounts.

[1016] Step 8:

[1017] Account suggestion and adjustment

[1018] The server displays the proposed account items on the user's operation screen.

[1019] The user reviews the proposed accounts and makes any necessary corrections.

[1020] Input: Proposed Account

[1021] Output: Accounts confirmed and modified by the user

[1022] Specific behavior: The user reviews the proposed accounts on the screen, makes any necessary corrections, and finally approves them.

[1023] Step 9:

[1024] Document verification and entry

[1025] The server retrieves relevant documents from a database and collates the information.

[1026] The server automatically enters the necessary information (subject, amount, tax information, etc.) based on the matching results.

[1027] Input: Related documents and accounts modified and approved by the user

[1028] Output: Auto-filled transaction information

[1029] How it works: The server searches for relevant documents in a database, collates the information, and automatically fills in the necessary transaction information.

[1030] Step 10:

[1031] Send to accounting system

[1032] The server converts the final transaction information into the appropriate format while maintaining consistency and transmits it to the external accounting system.

[1033] The server checks whether the transmission was successful and notifies the user of the result.

[1034] Input: Auto-filled transaction information

[1035] Output: Transaction information sent to an external accounting system and notification of the sending result

[1036] Specific operations: The server converts the transaction information into an appropriate format, sends the data to the external accounting system, confirms the success of the transmission, and notifies the user.

[1037] Step 11:

[1038] Emotion Engine Operation

[1039] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voice as the user interacts with the interface and recognize the user's emotional state.

[1040] The server dynamically adjusts the interface and feedback based on the perceived emotional state.

[1041] Input: User's facial expressions and voice data

[1042] Output: Dynamically adjusted interface and feedback

[1043] Specific operation: The server uses the emotion engine to monitor the user's emotional state and adjust the interface and feedback.

[1044] The above is the flow of processing of the program of this system.

[1045] (Application example 2)

[1046] Next, a description will be given of Application 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."

[1047] Modern accounting work involves manual document processing and determining accounting standards, which is extremely tedious and prone to human error. Furthermore, the mental burden of performing the work is significant, leading to stress. Therefore, along with streamlining accounting work, there is a demand for improved user interfaces to enhance the user experience.

[1048] 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 means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standards and tax decisions, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to the user and allowing the user to confirm or correct them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, and means for dynamically adjusting the operating experience using an emotion engine that recognizes the user's emotions. This enables more efficient accounting work and reduces user stress.

[1049] Definition of Terms

[1050] "Document" means accounting documents (e.g., contracts, purchase orders, invoices, etc.), whether in handwritten or printed form.

[1051] "Means for receiving" refers to the technology or process by which the server receives input from the user and saves the data in storage.

[1052] "Optical character recognition technology" is a technology that extracts character information from an image and converts it into text format.

[1053] The "means of extraction" is a process for extracting textual information from a document using optical character recognition technology.

[1054] "Means for analyzing and making accounting and tax judgments" refers to algorithms and logic for automatically determining applicable accounting and tax standards based on the extracted information.

[1055] The "means for proposing account items" is a process for selecting appropriate account categories based on the accounting standards of each company and presenting them to the user.

[1056] "Means for users to confirm and correct" refers to an interface that allows users to visually check the proposed account items and correct them if necessary.

[1057] "Means for matching and automatically entering transaction information" means a technology or process that matches related documents and automatically enters matching information.

[1058] The "means for transmitting to the accounting system" refers to a communication technology for transferring consistent transaction information to an external accounting system.

[1059] "Means for notifying transmission results" refers to the technology or process that notifies the user whether data transmission was successful.

[1060] An "emotion engine" is an algorithm or model for analyzing and recognizing a user's emotional state from their facial expressions or voice.

[1061] "Dynamic adjustment means" refers to a process of adaptively changing the operating procedures and display content of the user interface based on the analysis results of the emotion engine.

[1062] MODE FOR CARRYING OUT THE INVENTION

[1063] The present invention provides a system that automatically processes accounting documents, makes accounting and tax decisions, and proposes optimal account items. It also incorporates an emotion engine that recognizes user emotions to improve the user experience.

[1064] System configuration

[1065] 1. Receiving documents: The user scans or photographs accounting documents and uploads them to the system using a device (smartphone or PC). The server receives them and stores them in temporary storage.

[1066] 2. OCR Processing: The server uses optical character recognition technology (e.g., Tesseract OCR) to extract text information from the uploaded document.

[1067] 3. Information analysis: Based on the extracted text information, natural language processing technology is used to analyze and extract important data such as the contract number, contract date, amount, and counterparty, using existing pattern matching algorithms and AI technology.

[1068] 4. Accounting and tax decisions: The server automatically determines accounting standards and taxation based on the analyzed data. For example, it checks whether consumption tax applies and the payment due date.

[1069] 5. Account suggestion: The system refers to the chart of accounts set for each company and suggests appropriate accounts to the user. The user can review the suggestions and modify or approve them as necessary.

[1070] 6. Automatic entry of transaction information: The server checks the transaction information against other related documents and automatically enters it.

[1071] 7. Send to external accounting system: Integrate the final transaction information to the external accounting system and send the data. Check whether the sending was successful and notify the user of the result.

[1072] 8. Emotion Recognition: An emotion engine analyzes the user's facial expressions and voice to recognize their emotional state. Dynamically adjust the interface if stress levels are high.

[1073] Hardware and software used

[1074] Hardware: Smartphones, PCs, servers

[1075] software:

[1076] OpenCV: Used for image processing

[1077] Tesseract OCR: Character recognition

[1078] sklearn:Data standardization

[1079] keras: A neural network model for emotion recognition

[1080] Generative AI models and prompts: Natural language processing techniques

[1081] Unique financial information identification module: financial data extraction

[1082] Unique database module: data storage and collation

[1083] Specific examples

[1084] 1. Prompt: Please enter the path to the accounting document.

[1085] 2. Input example: C: / documents / invoice_2023.pdf

[1086] 3. Example output:

[1087] "Proposed Accounts: 'Purchases', 'Sales'"

[1088] "Users are frustrated. We're simplifying the process."

[1089] In this way, the present invention realizes efficient accounting work, reduces user stress, and provides a better operating experience.

[1090] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1091] Program processing flow

[1092] Step 1:

[1093] A user scans or photographs accounting documents (e.g., contracts, purchase orders, invoices, etc.) using a smartphone or PC, and uploads the image file to the system. At this time, the input for uploading is the path to the image file. The server receives the image file and stores it in temporary storage.

[1094] Step 2:

[1095] The server reads the saved image file and extracts the text information using optical character recognition technology (Tesseract OCR). The input is the image file, and the output is the text information in text format.

[1096] Step 3:

[1097] The server analyzes the extracted text information using natural language processing technology (generative AI model and prompt text) to extract important data such as the contract number, contract date, amount, counterparty, etc. The input is text information in text format, and the output is the extracted data (e.g., contract number, contract date, amount, counterparty, etc.).

[1098] Step 4:

[1099] The server makes accounting standards and tax decisions based on the extracted data. During this process, it automatically checks whether consumption tax applies, the payment due date, etc. The input is the extracted data, and the output is the accounting standards and tax decisions.

[1100] Step 5:

[1101] The server refers to the chart of accounts set for each company and suggests appropriate accounts to the user. At this time, a comparison is made with the chart of accounts database. The input is the accounting standards and the results of tax decisions, and the output is the suggested accounts.

[1102] Step 6:

[1103] The user reviews the proposed accounts and modifies and approves them as necessary. The input is the proposed accounts and the output is the accounts modified and approved by the user.

[1104] Step 7:

[1105] The server automatically inputs transaction information based on the account item approved by the user, checking it against other related documents (e.g., invoices, receipts, etc.) The input is the approved account item and related documents, and the output is the automatically input transaction information.

[1106] Step 8:

[1107] The server sends the final transaction information to the external accounting system. It checks whether the transmission was successful and notifies the user of the result. The input is the automatically entered transaction information, and the output is the transmission result to the accounting system.

[1108] Step 9:

[1109] While the user is operating the system, the server uses an emotion engine to analyze facial expressions and voice to recognize the user's emotional state. If stress levels are high, the server dynamically adjusts the interface and suggests ways to simplify the operation procedure. The input is the user's facial and voice data, and the output is the user's emotional state and the interface adjustment results.

[1110] 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.

[1111] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[1112] 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.

[1113] [Third embodiment]

[1114] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1115] 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.

[1116] 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).

[1117] 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.

[1118] 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.

[1119] 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).

[1120] 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.

[1121] 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.

[1122] 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.

[1123] 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.

[1124] 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.

[1125] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1126] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[1127] System Operation Overview

[1128] 1. Upload your documents

[1129] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[1130] 2. Document sorting and OCR processing

[1131] The server receives documents uploaded by users and stores them in temporary storage.

[1132] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[1133] The server sends the identified documents to an AI-OCR engine to extract the text information.

[1134] 3. Information analysis and extraction

[1135] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[1136] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[1137] 4. Clarifying accounting and tax issues

[1138] The server makes multiple accounting and tax decisions based on the stored data.

[1139] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[1140] 5. Account suggestion

[1141] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1142] The server displays the proposed account items on the user's operation screen.

[1143] The user can review the proposed accounts and approve or modify them as needed.

[1144] 6. Document verification and entry

[1145] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[1146] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[1147] 7. Send to accounting system

[1148] The server transmits the final transaction information in a consistent state to the external accounting system.

[1149] The server checks whether the transmission was successful and notifies the user of the result.

[1150] Specific examples

[1151] Contract processing example

[1152] 1. The user scans the contract and saves it in PDF format on their device.

[1153] 2. The user opens the system's upload function and uploads the saved contract to the server.

[1154] 3. The server receives the uploaded contract and stores it in temporary storage.

[1155] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[1156] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[1157] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[1158] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[1159] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[1160] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[1161] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1162] 11. The server checks whether the transmission was successful and notifies the user of the result.

[1163] In this way, the system of the present invention significantly improves the efficiency of accounting work and enables accurate accounting processing.

[1164] The processing flow will be explained below.

[1165] Step 1:

[1166] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[1167] Step 2:

[1168] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[1169] Step 3:

[1170] The server receives the uploaded documents and stores them in temporary storage.

[1171] Step 4:

[1172] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[1173] Step 5:

[1174] The server sends the identified documents to the AI-OCR engine to extract the text information.

[1175] Step 6:

[1176] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[1177] Step 7:

[1178] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[1179] Step 8:

[1180] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[1181] Step 9:

[1182] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1183] Step 10:

[1184] The server displays the selected account items on the user's operation screen.

[1185] Step 11:

[1186] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[1187] Step 12:

[1188] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[1189] Step 13:

[1190] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[1191] Step 14:

[1192] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1193] Step 15:

[1194] The server checks whether the transmission was successful and notifies the user of the result.

[1195] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders.

[1196] Example 1

[1197] Next, a description will be given of 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."

[1198] In accounting work, it is common to manually process documents such as contracts and purchase orders, which requires a great deal of time and effort. Manual data entry is prone to human error, which can lead to inaccurate accounting and tax decisions. Furthermore, efficient processing of vast amounts of accounting documents and accurate accounting procedures requires advanced technology, which places a heavy burden on many companies.

[1199] 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.

[1200] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for temporarily storing uploaded documents, means for transmitting to a corresponding optical character recognition engine based on the automatically identified documents, means for analyzing and parsing important information using natural language processing technology, and means for referencing a relational database that stores analyzed information each time. This enables automatic processing of accounting documents, thereby improving processing efficiency and accuracy.

[1201] The "means for receiving documents" is a function for receiving accounting documents uploaded by users and temporarily storing them.

[1202] "Optical character recognition technology" is a technology that automatically extracts text information from documents stored in digital formats such as images and PDFs.

[1203] The "means for analyzing extracted information" is a function for analyzing extracted character information using optical character recognition technology and extracting necessary data.

[1204] "Means for making multiple accounting standards and tax decisions" refers to a function that automatically makes various accounting standards and tax decisions based on extracted and analyzed data.

[1205] "Means for referencing account items set for each company" refers to a function for referencing an account item chart customized for each company and selecting appropriate account items.

[1206] The "means for proposing appropriate account items" is a function for proposing the most appropriate account items based on the analyzed information.

[1207] The "means for presenting the proposed account items to the user" is a function for displaying the selected account items to the user and enabling confirmation and correction.

[1208] "Means for user confirmation and correction" is a function that allows users to check the proposed account items and correct them if necessary.

[1209] "Means for comparing with related documents and automatically inputting transaction information" is a function for comparing existing related documents with uploaded documents and automatically inputting transaction information.

[1210] The "means for transmitting integrated transaction information to an external accounting system" is a function for transmitting the final integrated transaction information in a predetermined format to an external accounting system.

[1211] The "means for notifying the user of the transmission result" is a function for checking whether the data transmission to the external accounting system was successful and notifying the user of the result.

[1212] The "means for temporarily storing uploaded documents" is a function for temporarily storing documents uploaded by users in cloud storage or the like.

[1213] The "means for transmitting to a corresponding optical character recognition engine based on the automatically identified document" is a function for transmitting data to an appropriate optical character recognition engine depending on the type of automatically identified document.

[1214] "Means for analyzing and interpreting important information using natural language processing technology" refers to a function that uses natural language processing technology to accurately analyze important information from extracted text data.

[1215] "Means for referencing the relational database that stores analyzed information each time" refers to a function for referencing the relational database that stores analyzed information each time and retrieving the necessary data at the appropriate time.

[1216] The system of the present invention automatically processes accounting documents, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[1217] System Overview

[1218] This system is primarily composed of a server, user devices, and several software components. The server receives accounting documents, stores them, processes them with OCR, analyzes the information, proposes account items, collates documents, and sends the data to the accounting system. The user device scans accounting documents and uploads them to the system. The specific usage of each piece of hardware and software is explained below.

[1219] Document upload

[1220] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). Then, they open the system interface, select the digitized document file (PDF or image format), and click the upload button. The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3).

[1221] Document sorting and OCR processing

[1222] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). Based on the identification results, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The extracted text data is stored in a temporary database (e.g., MongoDB).

[1223] Information analysis and extraction

[1224] The server extracts the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The extracted important information is stored in a relational database (e.g., MySQL).

[1225] Clarifying accounting and tax issues

[1226] The server uses the stored data to make accounting and tax decisions, such as whether consumption tax applies, whether payment is made in advance or later, and whether payment is due, using a specific software library (e.g., PyDSTool).

[1227] Account suggestion

[1228] The server references a custom chart of accounts (e.g., a QuickBooks account list) configured for each company. Based on the analyzed information, it recommends appropriate accounts and displays them on the user's screen. The user can review the recommended accounts and modify or approve them as necessary.

[1229] Document verification and entry

[1230] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered to complete the required information.

[1231] Send to accounting system

[1232] The server finally converts the organized transaction information into the format of the ERP system (e.g., SAP ERP), sends the converted data to the external accounting system, checks the transmission results, and finally notifies the user of the transmission results.

[1233] Specific examples

[1234] Contract processing example

[1235] 1. The user scans the contract and saves it on their device.

[1236] 2. The user opens the system interface and uploads the contract file.

[1237] 3. The server receives the file and temporarily stores it in cloud storage.

[1238] 4. The server automatically identifies the file type as a contract using the cloud service API.

[1239] 5. The server sends the file to the OCR engine and extracts the character data.

[1240] 6. The server stores the extracted data in a temporary database.

[1241] 7. The server analyzes the data using natural language processing libraries and stores important information in a relational database.

[1242] 8. The server organizes accounting and tax standards and automatically determines tax issues.

[1243] 9. The server consults the chart of accounts and recommends the most appropriate accounts to the user.

[1244] 10. The user reviews the proposed accounts and makes any necessary modifications.

[1245] 11. The server compares the contract with other related documents and automatically fills in the required information.

[1246] 12. The server converts the data into ERP format and sends it to the accounting system.

[1247] 13. The server checks the transmission result and notifies the user.

[1248] Prompt Sentence Examples

[1249] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[1250] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[1251] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1252] Program processing steps

[1253] Step 1:

[1254] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). They select the digitized file (PDF or image format) in the system interface and click the upload button. The input is the physical file of the accounting document, and the output is the digital file saved on their device.

[1255] Step 2:

[1256] The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3). The input is the uploaded digital file, and the output is the file stored in the cloud storage.

[1257] Step 3:

[1258] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). The input is the file stored in cloud storage, and the output is the document type identification result. Based on the identification result, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The input is the document type and file, and the output is the extracted text data.

[1259] Step 4:

[1260] The server stores the character data obtained by OCR processing in a temporary database (e.g., MongoDB). The input is the character data extracted by OCR processing, and the output is the data stored in the temporary database.

[1261] Step 5:

[1262] The server takes the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The input is the stored text data, and the output is the analyzed important information. The extracted important information is stored in a relational database (e.g., MySQL). Specifically, the server uses SpaCy to tokenize the text data and applies a specific pattern matching algorithm.

[1263] Step 6:

[1264] The server uses the stored data to make accounting and tax decisions. For example, it uses a specific software library (e.g., PyDSTool) to perform automated decisions such as whether consumption tax applies or confirming payment due dates. The input is data stored in a relational database, and the output is the accounting and tax decisions.

[1265] Step 7:

[1266] The server references a custom chart of accounts configured for each company (e.g., a custom list of accounts in accounting software). The input is the parsed information and the chart of accounts, and the output is the recommendation of the best accounts. Specifically, the server reads the chart of accounts from the database and runs an algorithm to select the appropriate accounts.

[1267] Step 8:

[1268] The server displays the recommended accounts on the user's screen, and the user can review, modify, and approve them as necessary. The input is the recommended accounts, and the output is the accounts confirmed by the user.

[1269] Step 9:

[1270] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered and necessary information is completed. The input is the related documents and analyzed information, and the output is the completed transaction information.

[1271] Step 10:

[1272] The server finally converts the organized transaction information into the format of an ERP system (e.g., enterprise resource planning software). It then sends the converted data to an external accounting system and checks the transmission result. The input is the completed transaction information, and the output is the data converted into the ERP format and the transmission result. Finally, it notifies the user of the transmission result.

[1273] Prompt Sentence Examples

[1274] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[1275] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[1276] (Application example 1)

[1277] Next, a description will be given of Application 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."

[1278] Modern logistics centers handle a large number of delivery notes and invoices every day, and manually processing these documents requires a huge amount of time and effort. Manual input errors and oversights are also common, making it difficult to maintain the accuracy of accounting work. There is a need for a system that can solve these problems and improve the efficiency and accuracy of accounting work overall.

[1279] 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.

[1280] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each organization and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for scanning and uploading documents using a smartphone, and means for analyzing data using natural language processing technology and automatically extracting information. This enables efficient and accurate processing of many accounting documents at a logistics center, improving the efficiency and accuracy of the entire accounting operation.

[1281] "Documents" refer to paper or electronic documents such as contracts, purchase orders, invoices, and delivery notes that are handled in business activities.

[1282] "Means of receiving" refers to the process or equipment that transfers the document file uploaded by the user to the server and stores it.

[1283] "Optical character recognition technology" is a technology that extracts character information from scanned or photographed image data.

[1284] "Text information" refers to text information that has been converted into digital data from the contents of scanned or photographed documents.

[1285] "Analysis" is the process of extracting necessary data based on the extracted text information and automatically determining accounting standards and tax issues.

[1286] "Accounting standards" are the rules and methods that companies must follow when preparing financial statements.

[1287] "Tax judgment" is the process of making automated judgments based on rules and regulations regarding the calculation and application of taxes.

[1288] An "account item" is a classification item used to record a company's transactions.

[1289] "Means of suggestion" refers to the process by which the server selects appropriate account items and displays them to the user.

[1290] "Means for presenting to the user and for the user to confirm and modify" is the process of providing an interface for the user to view the proposed accounts and approve or modify them.

[1291] "Related Documents" refers to other contracts, invoices, etc. relating to the same transaction.

[1292] "Matching" is the process of checking whether information about the same transaction matches across different documents.

[1293] "Transaction information" refers to detailed data about a transaction, such as the date, amount, and counterparty.

[1294] "External accounting systems" refers to third-party accounting software or ERP systems used by a company.

[1295] The "transmission result" indicates whether the transaction information was successfully transmitted to the external accounting system.

[1296] A "smartphone" is a mobile device with advanced information processing capabilities and communication functions.

[1297] "Scanning" is the process of converting a paper document into digital image data.

[1298] "Uploading" is the process of transferring data stored on a local device to a remote system, such as a server.

[1299] "Natural language processing technology" refers to artificial intelligence technology for understanding and analyzing human language.

[1300] "Means for analyzing data and automatically extracting information" is the process of using natural language processing techniques to identify and extract important data from textual information.

[1301] The system of the present invention automatically processes accounting documents and suggests appropriate account items. This system is intended for use in logistics centers and pursues efficiency and accuracy using smartphones. The following describes the operation of the entire system and specific program processing.

[1302] System Operation Overview

[1303] 1. Upload your documents

[1304] Users can use their smartphone's camera to scan delivery notes and invoices and upload the image data to the system.

[1305] 2. Document sorting and OCR processing

[1306] The server receives the image files uploaded by the user and temporarily stores them.

[1307] The server uses optical character recognition technology (OCR) to extract text information from the image.

[1308] 3. Information analysis and extraction

[1309] The server analyzes the extracted text information and automatically extracts important information such as the transaction number, date, amount, and counterparty using natural language processing technology.

[1310] 4. Clarifying accounting and tax issues

[1311] The server makes multiple accounting and tax decisions, automatically checking, for example, whether consumption tax applies, whether payment is made in advance or later, and the payment due date.

[1312] 5. Account suggestion

[1313] The server refers to the chart of accounts set for each user and suggests appropriate accounts based on the extracted information.

[1314] The user reviews the proposed accounts and, if necessary, modifies and approves them.

[1315] 6. Document verification and entry

[1316] The server matches the relevant documents and automatically populates the transaction information.

[1317] 7. Send to accounting system

[1318] The server transmits the consolidated transaction information in a consistent manner to an external accounting system.

[1319] The server notifies the user of the transmission result.

[1320] Hardware and software used

[1321] Hardware: Smartphone (camera function), server

[1322] software:

[1323] OCR processing is performed using OpenCV and pytesseract.

[1324] Perform natural language processing using the Hugging Face Transformers library.

[1325] Build programs using Python.

[1326] Examples of concrete examples and prompts

[1327] Example 1:

[1328] If a distribution center manager wants to process multiple invoices in bulk:

[1329] Prompt: "Invoice scanned. Please analyze the data and suggest the appropriate accounting treatment."

[1330] Example 2:

[1331] At the end of the month, the accountant uploads the invoices and the accounting code is automatically suggested:

[1332] Prompt: "I uploaded an invoice. Please suggest a consumables account and confirm the payment due date."

[1333] In this way, the system of the present invention aims to improve the efficiency and accuracy of accounting operations at logistics centers.

[1334] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1335] Step 1:

[1336] Users scan accounting documents such as delivery notes and invoices using their smartphone cameras and upload them to the system. The input is the scanned image file, and the output is the image data transferred to the system.

[1337] Step 2:

[1338] The server receives image files uploaded by users and temporarily stores them in storage. The input is the uploaded image file, and the output is the stored image data.

[1339] Step 3:

[1340] The server extracts text information from images using optical character recognition (OCR). Specifically, the server uses OpenCV and pytesseract to generate text data from saved image files. The input is the saved image data, and the output is the extracted text data.

[1341] Step 4:

[1342] The server analyzes the extracted text and automatically extracts important information such as transaction number, date, amount, and counterparty using natural language processing (NLP). Specifically, it uses the Hugging Face Transformers library to identify the necessary data. The input is the text data extracted by OCR, and the output is the analyzed transaction information.

[1343] Step 5:

[1344] The server makes multiple accounting and tax decisions. It automatically determines whether consumption tax applies, whether payment is made in advance or later, and the payment due date. The input is analyzed transaction information, and the output is the results of accounting processing and tax decisions.

[1345] Step 6:

[1346] The server references the chart of accounts configured for each user and suggests appropriate accounts based on the extracted information. The input is the results of accounting and tax decisions, and the output is the suggested accounts.

[1347] Step 7:

[1348] The user reviews the proposed accounts and modifies or approves them as necessary. The input is the proposed accounts and the output is the modified or approved accounts.

[1349] Step 8:

[1350] The server automatically inputs transaction information by matching it with related documents. The input is the corrected or approved account and related document data, and the output is the consolidated transaction information.

[1351] Step 9:

[1352] The server sends the consolidated transaction information to an external accounting system. Specifically, it uses APIs to link data to other accounting software or ERP systems. The input is the consolidated transaction information, and the output is the transmission result to the external system.

[1353] Step 10:

[1354] The server notifies the user of the results of transmission to the external accounting system. The input is the transmission result, and the output is a notification message to the user.

[1355] In this way, the system of the present invention realizes automatic processing of accounting documents at a logistics center through each processing step.

[1356] 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.

[1357] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, sorts out accounting and tax issues, and proposes appropriate account headings. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the operating experience is improved. Below, the operation of the entire system and specific program processing are explained in natural language.

[1358] System Operation Overview

[1359] 1. Upload your documents

[1360] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[1361] 2. Document sorting and OCR processing

[1362] The server receives documents uploaded by users and stores them in temporary storage.

[1363] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[1364] The server sends the identified documents to an AI-OCR engine to extract the text information.

[1365] 3. Information analysis and extraction

[1366] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[1367] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[1368] 4. Clarifying accounting and tax issues

[1369] The server makes multiple accounting and tax decisions based on the stored data.

[1370] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[1371] 5. Account suggestion

[1372] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1373] The server displays the proposed account items on the user's operation screen.

[1374] The user can review the proposed accounts and approve or modify them as needed.

[1375] 6. Document verification and entry

[1376] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[1377] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[1378] 7. Send to accounting system

[1379] The server transmits the final transaction information in a consistent state to the external accounting system.

[1380] The server checks whether the transmission was successful and notifies the user of the result.

[1381] 8. How the Emotion Engine Works

[1382] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[1383] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[1384] If the user is in a high stress state, the server will make suggestions to simplify and automate the operation procedure.

[1385] Specific examples

[1386] Contract processing example

[1387] 1. The user scans the contract and saves it in PDF format on their device.

[1388] 2. The user opens the system's upload function and uploads the saved contract to the server.

[1389] 3. The server receives the uploaded contract and stores it in temporary storage.

[1390] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[1391] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[1392] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[1393] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[1394] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[1395] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[1396] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1397] 11. The server checks whether the transmission was successful and notifies the user of the result.

[1398] 12. The server uses an emotion engine to monitor the user's emotional state and simplifies the interface if stress levels are high.

[1399] In this way, the system of the present invention not only significantly improves the efficiency of accounting work and enables accurate accounting processing, but also improves the user's operating experience through its emotion engine.

[1400] The processing flow will be explained below.

[1401] Step 1:

[1402] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[1403] Step 2:

[1404] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[1405] Step 3:

[1406] The server receives the uploaded documents and stores them in temporary storage.

[1407] Step 4:

[1408] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[1409] Step 5:

[1410] The server sends the identified documents to the AI-OCR engine to extract the text information.

[1411] Step 6:

[1412] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[1413] Step 7:

[1414] The server uses existing pattern matching algorithms and natural language processing technology to accurately extract the necessary information and store it in a database.

[1415] Step 8:

[1416] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[1417] Step 9:

[1418] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1419] Step 10:

[1420] The server displays the selected account items on the user's operation screen.

[1421] Step 11:

[1422] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[1423] Step 12:

[1424] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[1425] Step 13:

[1426] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[1427] Step 14:

[1428] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1429] Step 15:

[1430] The server checks whether the transmission was successful and notifies the user of the result.

[1431] Step 16:

[1432] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[1433] Step 17:

[1434] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[1435] Step 18:

[1436] If the user is in a high stress state, the server will suggest ways to simplify and, if necessary, automate the operation procedure.

[1437] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders, and also recognizes the user's emotional state to improve the operating experience.

[1438] Example 2

[1439] Next, a description will be given of 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."

[1440] Processing accounting documents is often manual, time-consuming, and prone to errors. Furthermore, highly specialized knowledge is required to make decisions in accordance with specific accounting standards and tax issues, making it difficult to process documents efficiently and accurately. Furthermore, there is a lack of mechanisms to improve the user experience.

[1441] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standards and tax decisions, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to the user and allowing the user to confirm and correct them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, and means for recognizing the user's emotional state and dynamically adjusting the interface. This not only enables efficient and accurate processing of accounting documents, but also improves the user's operating experience.

[1442] The "means for receiving documents" is a function in which the server receives documents uploaded by the user using the terminal and stores them in temporary storage.

[1443] "Optical character recognition technology" is a technology that extracts character information from documents as digital data, a process that converts handwritten or printed text into a machine-readable format.

[1444] "Means for analyzing extracted information" refers to a function for identifying and organizing important information such as contract number, contract date, amount, and business partner based on text data extracted using optical character recognition technology.

[1445] "Means for making accounting standards and tax decisions" is a function that automatically makes appropriate decisions based on extracted information in accordance with multiple accounting standards and tax issues.

[1446] "Means for referencing and proposing account items set for each company" is a function that selects the most appropriate account items from each company's specific account item chart and proposes them to the user.

[1447] "Means for presenting proposed account items to the user and confirming / modifying them" refers to an interface that allows the server to display the proposed account items to the user, and for the user to confirm them and modify them as necessary.

[1448] The "means for automatically inputting transaction information by checking against related documents" is a function for automatically inputting accurate transaction information by checking against related documents in the database.

[1449] The "means for transmitting integrated transaction information to an external accounting system" is a function for converting final transaction information into an appropriate format and transmitting the data to an external accounting system.

[1450] The "means for notifying the user of the transmission result" is a function in which the server checks whether the data transmission to the external accounting system was successful and notifies the user of the result.

[1451] "Means for recognizing the user's emotional state and dynamically adjusting the interface" is a function that uses an emotion engine to analyze the user's emotional state and dynamically change the operation interface and feedback based on that.

[1452] MODE FOR CARRYING OUT THE INVENTION

[1453] The system of the present invention automatically processes accounting documents (contracts, purchase orders, invoices, etc.), makes accounting and tax decisions, and proposes appropriate account headings for the company. It also combines an emotion engine that recognizes the user's emotional state to improve the user experience.

[1454] System configuration

[1455] This system is configured using the following hardware and software.

[1456] 1. Server: The central unit that performs the main data processing. It is equipped with a high-performance processor and a large memory capacity. For data storage, it uses a database management system (e.g., MySQL, PostgreSQL).

[1457] 2. Terminal: A device operated by a user, such as a PC or smartphone. A browser or dedicated application is installed on the terminal.

[1458] 3. AI-OCR engine: A system that provides optical character recognition technology for extracting text information. A specific example of its use is the Google Cloud Vision API.

[1459] 4. NLP engine: An engine that uses natural language processing technology to improve the accuracy of extracted information. For example, spaCy is an example of this.

[1460] 5. Emotion Engine: An engine that recognizes user emotions and improves the operating experience, utilizing the Microsoft Emotion API.

[1461] System Operation Overview

[1462] The operation of the entire system will now be described in detail.

[1463] 1. Upload your documents

[1464] Users scan or photograph accounting documents and save them on their PC, smartphone, or other device, and then upload the documents to the server via the system's web interface or a dedicated app.

[1465] The terminal transmits a request to upload the selected file to the server.

[1466] 2. Receiving and sorting documents

[1467] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[1468] The server analyzes the stored files and automatically identifies their type, such as contract, invoice, purchase order, etc.

[1469] 3. Optical Character Recognition and Information Extraction

[1470] The server uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text information from the file.

[1471] The server receives the OCR processing results and temporarily stores the text data.

[1472] 4. Analysis of Information

[1473] The server analyzes the text data extracted from the OCR and identifies important information such as the contract number, contract date, amount, and business partner.

[1474] The server uses natural language processing (NLP) technology (e.g., spaCy) to accurately extract the required information and store it in the system's database.

[1475] 5. Clarifying accounting and tax issues

[1476] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[1477] 6. Accounting Proposal

[1478] The server looks up each company's specific chart of accounts and runs an algorithm to select the appropriate accounts.

[1479] The server displays the proposed account items on the user's operation screen so that the user can confirm and modify them.

[1480] 7. Document verification and entry

[1481] The server searches for relevant documents in the database, collates the information, and automatically enters the necessary transaction information (such as account, amount, and tax information).

[1482] 8. Send to accounting system

[1483] The server converts the final transaction information into the appropriate format and sends it to an external accounting system (e.g., SAP, QuickBooks).

[1484] The server checks whether the transmission was successful and notifies the user of the result.

[1485] 9. Emotion Engine Operation

[1486] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voices as the user operates the interface and recognize the user's emotional state.

[1487] The server dynamically adjusts the interface and feedback based on the user's emotional state. If the user is in a high stress state, the server suggests simplifying and automating the operation procedure.

[1488] Specific examples

[1489] Contract processing example

[1490] 1. The user scans the contract and saves it in PDF format on their device.

[1491] 2. The user activates the system's upload function and uploads the saved contract to the server.

[1492] 3. The device selects a file and sends an upload request to the server.

[1493] 4. The server receives the uploaded contract and stores it in temporary storage.

[1494] 5. The server automatically identifies the file as a contract and extracts the text data using an AI-OCR engine.

[1495] 6. The server analyzes the extracted data (contract number, contract date, amount, business partner, etc.) and stores it in a database.

[1496] 7. The server automatically determines whether consumption tax applies and the payment due date based on the stored data.

[1497] 8. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[1498] 9. The user reviews the proposed accounts and modifies and approves them as necessary.

[1499] 10. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[1500] 11. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1501] 12. The server confirms the transmission was successful and notifies the user of the result.

[1502] 13. The server uses an emotion engine to analyze the user's emotional state and simplifies the interface if the stress level is high.

[1503] Example of input prompt for generative AI model

[1504] Please explain in natural language how the following system works: The system works as follows:

[1505] 1. The user uploads the accounting document to the terminal.

[1506] 2. The server receives the uploaded document, automatically identifies it, performs OCR processing, and extracts the text information.

[1507] 3. The server analyzes the extracted information and stores important information such as the contract number, contract date, amount, and business partner in a database.

[1508] 4. The server organizes accounting standards and tax issues based on the stored information and suggests appropriate account items.

[1509] 5. The user reviews the proposed accounts, makes any necessary corrections, and approves them.

[1510] 6. The server sends the information to the accounting system, confirms success, and notifies the user.

[1511] 7. The server analyzes the user's emotions using an emotion engine to optimize the operating experience.

[1512] Based on this, please explain the overall operation of the system and the specific program processing.

[1513] The above is a detailed description of the "Mode for Carrying Out the Invention."

[1514] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1515] Step 1:

[1516] Document upload

[1517] Users scan or photograph accounting documents, save them as PDF or image files on their devices, and then upload the documents to the server via the system's web interface or a dedicated app.

[1518] Input: Accounting document file (PDF or image file)

[1519] Output: Upload request to server

[1520] Specific operation: The user opens the file selection dialog, selects an accounting document file, and presses the "Upload" button.

[1521] Step 2:

[1522] Receiving and temporarily storing documents

[1523] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[1524] Input: Uploaded accounting document file

[1525] Output: Files and their metadata stored in temporary storage

[1526] Specific operation: The server saves the received file in storage and records the metadata in the database.

[1527] Step 3:

[1528] Document sorting

[1529] The server analyzes the stored files and automatically identifies the type of document, such as a contract, invoice, or purchase order.

[1530] Input: A file saved in temporary storage

[1531] Output: Identified document type metadata

[1532] How it works: The server checks the file contents and determines the document type based on a pre-trained model.

[1533] Step 4:

[1534] Optical character recognition (OCR)

[1535] The server extracts text information from the file using an AI-OCR engine (e.g., Google Cloud Vision API).

[1536] Input: Identified accounting document file

[1537] Output: Extracted character information (text data)

[1538] Specific operation: The server sends the file to the AI-OCR engine and obtains the character information.

[1539] Step 5:

[1540] Analysis of information

[1541] The server analyzes the text data extracted from the OCR and extracts important information such as the contract number, contract date, amount, and business partner.

[1542] Input: Text data extracted from OCR

[1543] Output: Extracted important information (contract number, contract date, amount, business partner, etc.)

[1544] Specific operation: The server analyzes the text data using natural language processing (NLP) technology (e.g., spaCy) and extracts the necessary information.

[1545] Step 6:

[1546] Clarifying accounting and tax issues

[1547] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[1548] Input: Sensitive information stored in the database

[1549] Output: Organized accounting and tax information

[1550] Specific operation: The server automatically determines whether consumption tax applies, the payment due date, etc. in accordance with accounting standards and tax regulations.

[1551] Step 7:

[1552] Account suggestion

[1553] The server refers to the chart of accounts set for each company and selects the most appropriate account.

[1554] Input: Organized accounting and tax information

[1555] Output: Proposed accounts

[1556] How it works: The server runs an algorithm to suggest appropriate accounts from each company's chart of accounts.

[1557] Step 8:

[1558] Account suggestion and adjustment

[1559] The server displays the proposed account items on the user's operation screen.

[1560] The user reviews the proposed accounts and makes any necessary corrections.

[1561] Input: Proposed Account

[1562] Output: Accounts confirmed and modified by the user

[1563] Specific behavior: The user reviews the proposed accounts on the screen, makes any necessary corrections, and finally approves them.

[1564] Step 9:

[1565] Document verification and entry

[1566] The server retrieves relevant documents from a database and collates the information.

[1567] The server automatically enters the necessary information (subject, amount, tax information, etc.) based on the matching results.

[1568] Input: Related documents and accounts modified and approved by the user

[1569] Output: Auto-filled transaction information

[1570] How it works: The server searches for relevant documents in a database, collates the information, and automatically fills in the necessary transaction information.

[1571] Step 10:

[1572] Send to accounting system

[1573] The server converts the final transaction information into the appropriate format while maintaining consistency and transmits it to the external accounting system.

[1574] The server checks whether the transmission was successful and notifies the user of the result.

[1575] Input: Auto-filled transaction information

[1576] Output: Transaction information sent to an external accounting system and notification of the sending result

[1577] Specific operations: The server converts the transaction information into an appropriate format, sends the data to the external accounting system, confirms the success of the transmission, and notifies the user.

[1578] Step 11:

[1579] Emotion Engine Operation

[1580] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voice as the user interacts with the interface and recognize the user's emotional state.

[1581] The server dynamically adjusts the interface and feedback based on the perceived emotional state.

[1582] Input: User's facial expressions and voice data

[1583] Output: Dynamically adjusted interface and feedback

[1584] Specific operation: The server uses the emotion engine to monitor the user's emotional state and adjust the interface and feedback.

[1585] The above is the flow of processing of the program of this system.

[1586] (Application example 2)

[1587] Next, a description will be given of Application 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."

[1588] Modern accounting work involves manual document processing and determining accounting standards, which is extremely tedious and prone to human error. Furthermore, the mental burden of performing the work is significant, leading to stress. Therefore, along with streamlining accounting work, there is a demand for improved user interfaces to enhance the user experience.

[1589] 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 means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standards and tax decisions, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to the user and allowing the user to confirm or correct them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, and means for dynamically adjusting the operating experience using an emotion engine that recognizes the user's emotions. This enables more efficient accounting work and reduces user stress.

[1590] Definition of Terms

[1591] "Document" means accounting documents (e.g., contracts, purchase orders, invoices, etc.), whether in handwritten or printed form.

[1592] "Means for receiving" refers to the technology or process by which the server receives input from the user and saves the data in storage.

[1593] "Optical character recognition technology" is a technology that extracts character information from an image and converts it into text format.

[1594] The "means of extraction" is a process for extracting textual information from a document using optical character recognition technology.

[1595] "Means for analyzing and making accounting and tax judgments" refers to algorithms and logic for automatically determining applicable accounting and tax standards based on the extracted information.

[1596] The "means for proposing account items" is a process for selecting appropriate account categories based on the accounting standards of each company and presenting them to the user.

[1597] "Means for users to confirm and correct" refers to an interface that allows users to visually check the proposed account items and correct them if necessary.

[1598] "Means for matching and automatically entering transaction information" means a technology or process that matches related documents and automatically enters matching information.

[1599] The "means for transmitting to the accounting system" refers to a communication technology for transferring consistent transaction information to an external accounting system.

[1600] "Means for notifying transmission results" refers to the technology or process that notifies the user whether data transmission was successful.

[1601] An "emotion engine" is an algorithm or model for analyzing and recognizing a user's emotional state from their facial expressions or voice.

[1602] "Dynamic adjustment means" refers to a process of adaptively changing the operating procedures and display content of the user interface based on the analysis results of the emotion engine.

[1603] MODE FOR CARRYING OUT THE INVENTION

[1604] The present invention provides a system that automatically processes accounting documents, makes accounting and tax decisions, and proposes optimal account items. It also incorporates an emotion engine that recognizes user emotions to improve the user experience.

[1605] System configuration

[1606] 1. Receiving documents: The user scans or photographs accounting documents and uploads them to the system using a device (smartphone or PC). The server receives them and stores them in temporary storage.

[1607] 2. OCR Processing: The server uses optical character recognition technology (e.g., Tesseract OCR) to extract text information from the uploaded document.

[1608] 3. Information analysis: Based on the extracted text information, natural language processing technology is used to analyze and extract important data such as the contract number, contract date, amount, and counterparty, using existing pattern matching algorithms and AI technology.

[1609] 4. Accounting and tax decisions: The server automatically determines accounting standards and taxation based on the analyzed data. For example, it checks whether consumption tax applies and the payment due date.

[1610] 5. Account suggestion: The system refers to the chart of accounts set for each company and suggests appropriate accounts to the user. The user can review the suggestions and modify or approve them as necessary.

[1611] 6. Automatic entry of transaction information: The server checks the transaction information against other related documents and automatically enters it.

[1612] 7. Send to external accounting system: Integrate the final transaction information to the external accounting system and send the data. Check whether the sending was successful and notify the user of the result.

[1613] 8. Emotion Recognition: An emotion engine analyzes the user's facial expressions and voice to recognize their emotional state. Dynamically adjust the interface if stress levels are high.

[1614] Hardware and software used

[1615] Hardware: Smartphones, PCs, servers

[1616] software:

[1617] OpenCV: Used for image processing

[1618] Tesseract OCR: Character recognition

[1619] sklearn:Data standardization

[1620] keras: A neural network model for emotion recognition

[1621] Generative AI models and prompts: Natural language processing techniques

[1622] Unique financial information identification module: financial data extraction

[1623] Unique database module: data storage and collation

[1624] Specific examples

[1625] 1. Prompt: Please enter the path to the accounting document.

[1626] 2. Input example: C: / documents / invoice_2023.pdf

[1627] 3. Example output:

[1628] "Proposed Accounts: 'Purchases', 'Sales'"

[1629] "Users are frustrated. We're simplifying the process."

[1630] In this way, the present invention realizes efficient accounting work, reduces user stress, and provides a better operating experience.

[1631] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1632] Program processing flow

[1633] Step 1:

[1634] A user scans or photographs accounting documents (e.g., contracts, purchase orders, invoices, etc.) using a smartphone or PC, and uploads the image file to the system. At this time, the input for uploading is the path to the image file. The server receives the image file and stores it in temporary storage.

[1635] Step 2:

[1636] The server reads the saved image file and extracts the text information using optical character recognition technology (Tesseract OCR). The input is the image file, and the output is the text information in text format.

[1637] Step 3:

[1638] The server analyzes the extracted text information using natural language processing technology (generative AI model and prompt text) to extract important data such as the contract number, contract date, amount, counterparty, etc. The input is text information in text format, and the output is the extracted data (e.g., contract number, contract date, amount, counterparty, etc.).

[1639] Step 4:

[1640] The server makes accounting standards and tax decisions based on the extracted data. During this process, it automatically checks whether consumption tax applies, the payment due date, etc. The input is the extracted data, and the output is the accounting standards and tax decisions.

[1641] Step 5:

[1642] The server refers to the chart of accounts set for each company and suggests appropriate accounts to the user. At this time, a comparison is made with the chart of accounts database. The input is the accounting standards and the results of tax decisions, and the output is the suggested accounts.

[1643] Step 6:

[1644] The user reviews the proposed accounts and modifies and approves them as necessary. The input is the proposed accounts and the output is the accounts modified and approved by the user.

[1645] Step 7:

[1646] The server automatically inputs transaction information based on the account item approved by the user, checking it against other related documents (e.g., invoices, receipts, etc.) The input is the approved account item and related documents, and the output is the automatically input transaction information.

[1647] Step 8:

[1648] The server sends the final transaction information to the external accounting system. It checks whether the transmission was successful and notifies the user of the result. The input is the automatically entered transaction information, and the output is the transmission result to the accounting system.

[1649] Step 9:

[1650] While the user is operating the system, the server uses an emotion engine to analyze facial expressions and voice to recognize the user's emotional state. If stress levels are high, the server dynamically adjusts the interface and suggests ways to simplify the operation procedure. The input is the user's facial and voice data, and the output is the user's emotional state and the interface adjustment results.

[1651] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 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.

[1652] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[1653] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1654] [Fourth embodiment]

[1655] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1656] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1657] 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).

[1658] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. 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 control target 443 are also connected to the bus 52.

[1659] 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.

[1660] 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).

[1661] 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.

[1662] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1663] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, 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.

[1664] 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.

[1665] 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.

[1666] In the robot 414, the processor 46 performs the reception output process. 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.

[1667] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1668] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[1669] System Operation Overview

[1670] 1. Upload your documents

[1671] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[1672] 2. Document sorting and OCR processing

[1673] The server receives documents uploaded by users and stores them in temporary storage.

[1674] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[1675] The server sends the identified documents to an AI-OCR engine to extract the text information.

[1676] 3. Information analysis and extraction

[1677] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[1678] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[1679] 4. Clarifying accounting and tax issues

[1680] The server makes multiple accounting and tax decisions based on the stored data.

[1681] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[1682] 5. Account suggestion

[1683] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1684] The server displays the proposed account items on the user's operation screen.

[1685] The user can review the proposed accounts and approve or modify them as needed.

[1686] 6. Document verification and entry

[1687] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[1688] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[1689] 7. Send to accounting system

[1690] The server transmits the final transaction information in a consistent state to the external accounting system.

[1691] The server checks whether the transmission was successful and notifies the user of the result.

[1692] Specific examples

[1693] Contract processing example

[1694] 1. The user scans the contract and saves it in PDF format on their device.

[1695] 2. The user opens the system's upload function and uploads the saved contract to the server.

[1696] 3. The server receives the uploaded contract and stores it in temporary storage.

[1697] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[1698] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[1699] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[1700] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[1701] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[1702] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[1703] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1704] 11. The server checks whether the transmission was successful and notifies the user of the result.

[1705] In this way, the system of the present invention significantly improves the efficiency of accounting work and enables accurate accounting processing.

[1706] The processing flow will be explained below.

[1707] Step 1:

[1708] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[1709] Step 2:

[1710] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[1711] Step 3:

[1712] The server receives the uploaded documents and stores them in temporary storage.

[1713] Step 4:

[1714] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[1715] Step 5:

[1716] The server sends the identified documents to the AI-OCR engine to extract the text information.

[1717] Step 6:

[1718] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[1719] Step 7:

[1720] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[1721] Step 8:

[1722] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[1723] Step 9:

[1724] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1725] Step 10:

[1726] The server displays the selected account items on the user's operation screen.

[1727] Step 11:

[1728] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[1729] Step 12:

[1730] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[1731] Step 13:

[1732] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[1733] Step 14:

[1734] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1735] Step 15:

[1736] The server checks whether the transmission was successful and notifies the user of the result.

[1737] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders.

[1738] Example 1

[1739] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1740] In accounting work, it is common to manually process documents such as contracts and purchase orders, which requires a great deal of time and effort. Manual data entry is prone to human error, which can lead to inaccurate accounting and tax decisions. Furthermore, efficient processing of vast amounts of accounting documents and accurate accounting procedures requires advanced technology, which places a heavy burden on many companies.

[1741] 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.

[1742] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for temporarily storing uploaded documents, means for transmitting to a corresponding optical character recognition engine based on the automatically identified documents, means for analyzing and parsing important information using natural language processing technology, and means for referencing a relational database that stores analyzed information each time. This enables automatic processing of accounting documents, thereby improving processing efficiency and accuracy.

[1743] The "means for receiving documents" is a function for receiving accounting documents uploaded by users and temporarily storing them.

[1744] "Optical character recognition technology" is a technology that automatically extracts text information from documents stored in digital formats such as images and PDFs.

[1745] The "means for analyzing extracted information" is a function for analyzing extracted character information using optical character recognition technology and extracting necessary data.

[1746] "Means for making multiple accounting standards and tax decisions" refers to a function that automatically makes various accounting standards and tax decisions based on extracted and analyzed data.

[1747] "Means for referencing account items set for each company" refers to a function for referencing an account item chart customized for each company and selecting appropriate account items.

[1748] The "means for proposing appropriate account items" is a function for proposing the most appropriate account items based on the analyzed information.

[1749] The "means for presenting the proposed account items to the user" is a function for displaying the selected account items to the user and enabling confirmation and correction.

[1750] "Means for user confirmation and correction" is a function that allows users to check the proposed account items and correct them if necessary.

[1751] "Means for comparing with related documents and automatically inputting transaction information" is a function for comparing existing related documents with uploaded documents and automatically inputting transaction information.

[1752] The "means for transmitting integrated transaction information to an external accounting system" is a function for transmitting the final integrated transaction information in a predetermined format to an external accounting system.

[1753] The "means for notifying the user of the transmission result" is a function for checking whether the data transmission to the external accounting system was successful and notifying the user of the result.

[1754] The "means for temporarily storing uploaded documents" is a function for temporarily storing documents uploaded by users in cloud storage or the like.

[1755] The "means for transmitting to a corresponding optical character recognition engine based on the automatically identified document" is a function for transmitting data to an appropriate optical character recognition engine depending on the type of automatically identified document.

[1756] "Means for analyzing and interpreting important information using natural language processing technology" refers to a function that uses natural language processing technology to accurately analyze important information from extracted text data.

[1757] "Means for referencing the relational database that stores analyzed information each time" refers to a function for referencing the relational database that stores analyzed information each time and retrieving the necessary data at the appropriate time.

[1758] The system of the present invention automatically processes accounting documents, organizes accounting and tax issues, and proposes appropriate account headings. Below, the operation of the entire system and specific program processing are explained in natural language.

[1759] System Overview

[1760] This system is primarily composed of a server, user devices, and several software components. The server receives accounting documents, stores them, processes them with OCR, analyzes the information, proposes account items, collates documents, and sends the data to the accounting system. The user device scans accounting documents and uploads them to the system. The specific usage of each piece of hardware and software is explained below.

[1761] Document upload

[1762] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). Then, they open the system interface, select the digitized document file (PDF or image format), and click the upload button. The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3).

[1763] Document sorting and OCR processing

[1764] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). Based on the identification results, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The extracted text data is stored in a temporary database (e.g., MongoDB).

[1765] Information analysis and extraction

[1766] The server extracts the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The extracted important information is stored in a relational database (e.g., MySQL).

[1767] Clarifying accounting and tax issues

[1768] The server uses the stored data to make accounting and tax decisions, such as whether consumption tax applies, whether payment is made in advance or later, and whether payment is due, using a specific software library (e.g., PyDSTool).

[1769] Account suggestion

[1770] The server references a custom chart of accounts (e.g., a QuickBooks account list) configured for each company. Based on the analyzed information, it recommends appropriate accounts and displays them on the user's screen. The user can review the recommended accounts and modify or approve them as necessary.

[1771] Document verification and entry

[1772] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered to complete the required information.

[1773] Send to accounting system

[1774] The server finally converts the organized transaction information into the format of the ERP system (e.g., SAP ERP), sends the converted data to the external accounting system, checks the transmission results, and finally notifies the user of the transmission results.

[1775] Specific examples

[1776] Contract processing example

[1777] 1. The user scans the contract and saves it on their device.

[1778] 2. The user opens the system interface and uploads the contract file.

[1779] 3. The server receives the file and temporarily stores it in cloud storage.

[1780] 4. The server automatically identifies the file type as a contract using the cloud service API.

[1781] 5. The server sends the file to the OCR engine and extracts the character data.

[1782] 6. The server stores the extracted data in a temporary database.

[1783] 7. The server analyzes the data using natural language processing libraries and stores important information in a relational database.

[1784] 8. The server organizes accounting and tax standards and automatically determines tax issues.

[1785] 9. The server consults the chart of accounts and recommends the most appropriate accounts to the user.

[1786] 10. The user reviews the proposed accounts and makes any necessary modifications.

[1787] 11. The server compares the contract with other related documents and automatically fills in the required information.

[1788] 12. The server converts the data into ERP format and sends it to the accounting system.

[1789] 13. The server checks the transmission result and notifies the user.

[1790] Prompt Sentence Examples

[1791] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[1792] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[1793] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1794] Program processing steps

[1795] Step 1:

[1796] The user digitizes the accounting document using a scanner or smartphone camera and saves it on their device (PC or smartphone). They select the digitized file (PDF or image format) in the system interface and click the upload button. The input is the physical file of the accounting document, and the output is the digital file saved on their device.

[1797] Step 2:

[1798] The server receives the upload request and temporarily stores the accounting document file in cloud storage (e.g., Amazon S3). The input is the uploaded digital file, and the output is the file stored in the cloud storage.

[1799] Step 3:

[1800] The server retrieves the temporarily stored file and automatically identifies the document type (contract, purchase order, invoice, etc.) using a cloud service API (e.g., Google Cloud Vision API). The input is the file stored in cloud storage, and the output is the document type identification result. Based on the identification result, the document is sent to an AI-OCR engine (e.g., Tesseract OCR) to extract text information. The input is the document type and file, and the output is the extracted text data.

[1801] Step 4:

[1802] The server stores the character data obtained by OCR processing in a temporary database (e.g., MongoDB). The input is the character data extracted by OCR processing, and the output is the data stored in the temporary database.

[1803] Step 5:

[1804] The server takes the text data extracted by OCR and analyzes important information such as the contract number, contract date, amount, and counterparty using a natural language processing library (e.g., SpaCy). The input is the stored text data, and the output is the analyzed important information. The extracted important information is stored in a relational database (e.g., MySQL). Specifically, the server uses SpaCy to tokenize the text data and applies a specific pattern matching algorithm.

[1805] Step 6:

[1806] The server uses the stored data to make accounting and tax decisions. For example, it uses a specific software library (e.g., PyDSTool) to perform automated decisions such as whether consumption tax applies or confirming payment due dates. The input is data stored in a relational database, and the output is the accounting and tax decisions.

[1807] Step 7:

[1808] The server references a custom chart of accounts configured for each company (e.g., a custom list of accounts in accounting software). The input is the parsed information and the chart of accounts, and the output is the recommendation of the best accounts. Specifically, the server reads the chart of accounts from the database and runs an algorithm to select the appropriate accounts.

[1809] Step 8:

[1810] The server displays the recommended accounts on the user's screen, and the user can review, modify, and approve them as necessary. The input is the recommended accounts, and the output is the accounts confirmed by the user.

[1811] Step 9:

[1812] The server retrieves other related accounting documents (e.g., shipping slips and receipts) from the database and performs matching. Matching information is automatically entered and necessary information is completed. The input is the related documents and analyzed information, and the output is the completed transaction information.

[1813] Step 10:

[1814] The server finally converts the organized transaction information into the format of an ERP system (e.g., enterprise resource planning software). It then sends the converted data to an external accounting system and checks the transmission result. The input is the completed transaction information, and the output is the data converted into the ERP format and the transmission result. Finally, it notifies the user of the transmission result.

[1815] Prompt Sentence Examples

[1816] Scan the contract, save it as a PDF, and upload it. Then, use an OCR engine to extract text information and analyze data such as the contract number, contract date, amount, and counterparty. Finally, automatically send it to your accounting system.

[1817] In this way, this system automates accounting operations and uses advanced technology to improve processing efficiency and accuracy.

[1818] (Application example 1)

[1819] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1820] Modern logistics centers handle a large number of delivery notes and invoices every day, and manually processing these documents requires a huge amount of time and effort. Manual input errors and oversights are also common, making it difficult to maintain the accuracy of accounting work. There is a need for a system that can solve these problems and improve the efficiency and accuracy of accounting work overall.

[1821] 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.

[1822] In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standard and tax judgments, means for referencing account items set for each organization and proposing appropriate account items, means for presenting the proposed account items to a user and allowing the user to confirm or modify them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, means for scanning and uploading documents using a smartphone, and means for analyzing data using natural language processing technology and automatically extracting information. This enables efficient and accurate processing of many accounting documents at a logistics center, improving the efficiency and accuracy of the entire accounting operation.

[1823] "Documents" refer to paper or electronic documents such as contracts, purchase orders, invoices, and delivery notes that are handled in business activities.

[1824] "Means of receiving" refers to the process or equipment that transfers the document file uploaded by the user to the server and stores it.

[1825] "Optical character recognition technology" is a technology that extracts character information from scanned or photographed image data.

[1826] "Text information" refers to text information that has been converted into digital data from the contents of scanned or photographed documents.

[1827] "Analysis" is the process of extracting necessary data based on the extracted text information and automatically determining accounting standards and tax issues.

[1828] "Accounting standards" are the rules and methods that companies must follow when preparing financial statements.

[1829] "Tax judgment" is the process of making automated judgments based on rules and regulations regarding the calculation and application of taxes.

[1830] An "account item" is a classification item used to record a company's transactions.

[1831] "Means of suggestion" refers to the process by which the server selects appropriate account items and displays them to the user.

[1832] "Means for presenting to the user and for the user to confirm and modify" is the process of providing an interface for the user to view the proposed accounts and approve or modify them.

[1833] "Related Documents" refers to other contracts, invoices, etc. relating to the same transaction.

[1834] "Matching" is the process of checking whether information about the same transaction matches across different documents.

[1835] "Transaction information" refers to detailed data about a transaction, such as the date, amount, and counterparty.

[1836] "External accounting systems" refers to third-party accounting software or ERP systems used by a company.

[1837] The "transmission result" indicates whether the transaction information was successfully transmitted to the external accounting system.

[1838] A "smartphone" is a mobile device with advanced information processing capabilities and communication functions.

[1839] "Scanning" is the process of converting a paper document into digital image data.

[1840] "Uploading" is the process of transferring data stored on a local device to a remote system, such as a server.

[1841] "Natural language processing technology" refers to artificial intelligence technology for understanding and analyzing human language.

[1842] "Means for analyzing data and automatically extracting information" is the process of using natural language processing techniques to identify and extract important data from textual information.

[1843] The system of the present invention automatically processes accounting documents and suggests appropriate account items. This system is intended for use in logistics centers and pursues efficiency and accuracy using smartphones. The following describes the operation of the entire system and specific program processing.

[1844] System Operation Overview

[1845] 1. Upload your documents

[1846] Users can use their smartphone's camera to scan delivery notes and invoices and upload the image data to the system.

[1847] 2. Document sorting and OCR processing

[1848] The server receives the image files uploaded by the user and temporarily stores them.

[1849] The server uses optical character recognition technology (OCR) to extract text information from the image.

[1850] 3. Information analysis and extraction

[1851] The server analyzes the extracted text information and automatically extracts important information such as the transaction number, date, amount, and counterparty using natural language processing technology.

[1852] 4. Clarifying accounting and tax issues

[1853] The server makes multiple accounting and tax decisions, automatically checking, for example, whether consumption tax applies, whether payment is made in advance or later, and the payment due date.

[1854] 5. Account suggestion

[1855] The server refers to the chart of accounts set for each user and suggests appropriate accounts based on the extracted information.

[1856] The user reviews the proposed accounts and, if necessary, modifies and approves them.

[1857] 6. Document verification and entry

[1858] The server matches the relevant documents and automatically populates the transaction information.

[1859] 7. Send to accounting system

[1860] The server transmits the consolidated transaction information in a consistent manner to an external accounting system.

[1861] The server notifies the user of the transmission result.

[1862] Hardware and software used

[1863] Hardware: Smartphone (camera function), server

[1864] software:

[1865] OCR processing is performed using OpenCV and pytesseract.

[1866] Perform natural language processing using the Hugging Face Transformers library.

[1867] Build programs using Python.

[1868] Examples of concrete examples and prompts

[1869] Example 1:

[1870] If a distribution center manager wants to process multiple invoices in bulk:

[1871] Prompt: "Invoice scanned. Please analyze the data and suggest the appropriate accounting treatment."

[1872] Example 2:

[1873] At the end of the month, the accountant uploads the invoices and the accounting code is automatically suggested:

[1874] Prompt: "I uploaded an invoice. Please suggest a consumables account and confirm the payment due date."

[1875] In this way, the system of the present invention aims to improve the efficiency and accuracy of accounting operations at logistics centers.

[1876] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1877] Step 1:

[1878] Users scan accounting documents such as delivery notes and invoices using their smartphone cameras and upload them to the system. The input is the scanned image file, and the output is the image data transferred to the system.

[1879] Step 2:

[1880] The server receives image files uploaded by users and temporarily stores them in storage. The input is the uploaded image file, and the output is the stored image data.

[1881] Step 3:

[1882] The server extracts text information from images using optical character recognition (OCR). Specifically, the server uses OpenCV and pytesseract to generate text data from saved image files. The input is the saved image data, and the output is the extracted text data.

[1883] Step 4:

[1884] The server analyzes the extracted text and automatically extracts important information such as transaction number, date, amount, and counterparty using natural language processing (NLP). Specifically, it uses the Hugging Face Transformers library to identify the necessary data. The input is the text data extracted by OCR, and the output is the analyzed transaction information.

[1885] Step 5:

[1886] The server makes multiple accounting and tax decisions. It automatically determines whether consumption tax applies, whether payment is made in advance or later, and the payment due date. The input is analyzed transaction information, and the output is the results of accounting processing and tax decisions.

[1887] Step 6:

[1888] The server references the chart of accounts configured for each user and suggests appropriate accounts based on the extracted information. The input is the results of accounting and tax decisions, and the output is the suggested accounts.

[1889] Step 7:

[1890] The user reviews the proposed accounts and modifies or approves them as necessary. The input is the proposed accounts and the output is the modified or approved accounts.

[1891] Step 8:

[1892] The server automatically inputs transaction information by matching it with related documents. The input is the corrected or approved account and related document data, and the output is the consolidated transaction information.

[1893] Step 9:

[1894] The server sends the consolidated transaction information to an external accounting system. Specifically, it uses APIs to link data to other accounting software or ERP systems. The input is the consolidated transaction information, and the output is the transmission result to the external system.

[1895] Step 10:

[1896] The server notifies the user of the results of transmission to the external accounting system. The input is the transmission result, and the output is a notification message to the user.

[1897] In this way, the system of the present invention realizes automatic processing of accounting documents at a logistics center through each processing step.

[1898] 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.

[1899] The system of the present invention automatically processes accounting documents such as contracts and purchase orders, sorts out accounting and tax issues, and proposes appropriate account headings. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the operating experience is improved. Below, the operation of the entire system and specific program processing are explained in natural language.

[1900] System Operation Overview

[1901] 1. Upload your documents

[1902] Users upload scanned or photographed accounting documents to the system using a terminal (PC, smartphone, etc.).

[1903] 2. Document sorting and OCR processing

[1904] The server receives documents uploaded by users and stores them in temporary storage.

[1905] The server automatically identifies the document type as a contract, purchase order, invoice, etc.

[1906] The server sends the identified documents to an AI-OCR engine to extract the text information.

[1907] 3. Information analysis and extraction

[1908] The server receives the data returned by the OCR engine and parses it for important information such as the contract number, contract date, amount, and counterparty.

[1909] The server uses existing pattern matching algorithms and natural language processing techniques to accurately extract the required information and store it in a database.

[1910] 4. Clarifying accounting and tax issues

[1911] The server makes multiple accounting and tax decisions based on the stored data.

[1912] The server automatically checks, for example, whether consumption tax is applied, whether payment is made in advance or later, and the payment due date.

[1913] 5. Account suggestion

[1914] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1915] The server displays the proposed account items on the user's operation screen.

[1916] The user can review the proposed accounts and approve or modify them as needed.

[1917] 6. Document verification and entry

[1918] The server retrieves relevant documents (e.g., release slips and acceptance slips) from a database and collates the information.

[1919] The server automatically populates the appropriate document with the subject line item, amount, and tax information.

[1920] 7. Send to accounting system

[1921] The server transmits the final transaction information in a consistent state to the external accounting system.

[1922] The server checks whether the transmission was successful and notifies the user of the result.

[1923] 8. How the Emotion Engine Works

[1924] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[1925] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[1926] If the user is in a high stress state, the server will make suggestions to simplify and automate the operation procedure.

[1927] Specific examples

[1928] Contract processing example

[1929] 1. The user scans the contract and saves it in PDF format on their device.

[1930] 2. The user opens the system's upload function and uploads the saved contract to the server.

[1931] 3. The server receives the uploaded contract and stores it in temporary storage.

[1932] 4. The server automatically identifies the document as a contract and sends it to the AI-OCR engine.

[1933] 5. The server analyzes the data extracted by OCR processing (contract number, contract date, amount, counterparty, etc.) and stores it in a database.

[1934] 6. The server organizes accounting standards and tax issues based on the stored data and automatically determines whether consumption tax applies and the payment due date.

[1935] 7. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[1936] 8. The user reviews the proposed accounts, amends them as necessary, and approves them.

[1937] 9. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[1938] 10. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1939] 11. The server checks whether the transmission was successful and notifies the user of the result.

[1940] 12. The server uses an emotion engine to monitor the user's emotional state and simplifies the interface if stress levels are high.

[1941] In this way, the system of the present invention not only significantly improves the efficiency of accounting work and enables accurate accounting processing, but also improves the user's operating experience through its emotion engine.

[1942] The processing flow will be explained below.

[1943] Step 1:

[1944] The user scans or photographs documents such as contracts or purchase orders and saves them on the device.

[1945] Step 2:

[1946] The user opens the upload screen of the system and uploads the scanned or saved document to the server.

[1947] Step 3:

[1948] The server receives the uploaded documents and stores them in temporary storage.

[1949] Step 4:

[1950] The server automatically identifies the type of document uploaded and categorizes it as a contract, purchase order, invoice, etc.

[1951] Step 5:

[1952] The server sends the identified documents to the AI-OCR engine to extract the text information.

[1953] Step 6:

[1954] The server receives the data returned by the OCR engine and analyzes it for important information such as the contract number, contract date, amount, and counterparty.

[1955] Step 7:

[1956] The server uses existing pattern matching algorithms and natural language processing technology to accurately extract the necessary information and store it in a database.

[1957] Step 8:

[1958] Based on the data stored on the server, accounting standards and tax decisions are made, such as whether consumption tax applies, whether payment is made in advance or on a deferred basis, and confirmation of payment due dates.

[1959] Step 9:

[1960] The server refers to the chart of accounts set for each company and selects the account that best suits the extracted information.

[1961] Step 10:

[1962] The server displays the selected account items on the user's operation screen.

[1963] Step 11:

[1964] The user reviews the proposed accounts, modifies them if necessary, and approves them.

[1965] Step 12:

[1966] The server retrieves relevant documents (clearance certificates, inspection certificates, etc.) from the database and checks them.

[1967] Step 13:

[1968] The server automatically fills in the subject line item, amount, and tax information for the appropriate document.

[1969] Step 14:

[1970] The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[1971] Step 15:

[1972] The server checks whether the transmission was successful and notifies the user of the result.

[1973] Step 16:

[1974] The server uses an emotion engine to analyze the user's facial expressions and voice when operating the interface, and recognizes the user's emotional state.

[1975] Step 17:

[1976] The interface and feedback are dynamically adjusted based on the emotional state recognized by the server.

[1977] Step 18:

[1978] If the user is in a high stress state, the server will suggest ways to simplify and, if necessary, automate the operation procedure.

[1979] In this way, through each step, the system ensures efficient and accurate processing of contracts and purchase orders, and also recognizes the user's emotional state to improve the operating experience.

[1980] Example 2

[1981] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1982] Processing accounting documents is often manual, time-consuming, and prone to errors. Furthermore, highly specialized knowledge is required to make decisions in accordance with specific accounting standards and tax issues, making it difficult to process documents efficiently and accurately. Furthermore, there is a lack of mechanisms to improve the user experience.

[1983] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving documents, means for extracting character information using optical character recognition technology, means for analyzing the extracted information and making multiple accounting standards and tax decisions, means for referencing account items set for each company and proposing appropriate account items, means for presenting the proposed account items to the user and allowing the user to confirm and correct them, means for comparing with related documents and automatically inputting transaction information, means for transmitting the integrated transaction information to an external accounting system, means for notifying the user of the transmission result, and means for recognizing the user's emotional state and dynamically adjusting the interface. This not only enables efficient and accurate processing of accounting documents, but also improves the user's operating experience.

[1984] The "means for receiving documents" is a function in which the server receives documents uploaded by the user using the terminal and stores them in temporary storage.

[1985] "Optical character recognition technology" is a technology that extracts character information from documents as digital data, a process that converts handwritten or printed text into a machine-readable format.

[1986] "Means for analyzing extracted information" refers to a function for identifying and organizing important information such as contract number, contract date, amount, and business partner based on text data extracted using optical character recognition technology.

[1987] "Means for making accounting standards and tax decisions" is a function that automatically makes appropriate decisions based on extracted information in accordance with multiple accounting standards and tax issues.

[1988] "Means for referencing and proposing account items set for each company" is a function that selects the most appropriate account items from each company's specific account item chart and proposes them to the user.

[1989] "Means for presenting proposed account items to the user and confirming / modifying them" refers to an interface that allows the server to display the proposed account items to the user, and for the user to confirm them and modify them as necessary.

[1990] The "means for automatically inputting transaction information by checking against related documents" is a function for automatically inputting accurate transaction information by checking against related documents in the database.

[1991] The "means for transmitting integrated transaction information to an external accounting system" is a function for converting final transaction information into an appropriate format and transmitting the data to an external accounting system.

[1992] The "means for notifying the user of the transmission result" is a function in which the server checks whether the data transmission to the external accounting system was successful and notifies the user of the result.

[1993] "Means for recognizing the user's emotional state and dynamically adjusting the interface" is a function that uses an emotion engine to analyze the user's emotional state and dynamically change the operation interface and feedback based on that.

[1994] MODE FOR CARRYING OUT THE INVENTION

[1995] The system of the present invention automatically processes accounting documents (contracts, purchase orders, invoices, etc.), makes accounting and tax decisions, and proposes appropriate account headings for the company. It also combines an emotion engine that recognizes the user's emotional state to improve the user experience.

[1996] System configuration

[1997] This system is configured using the following hardware and software.

[1998] 1. Server: The central unit that performs the main data processing. It is equipped with a high-performance processor and a large memory capacity. For data storage, it uses a database management system (e.g., MySQL, PostgreSQL).

[1999] 2. Terminal: A device operated by a user, such as a PC or smartphone. A browser or dedicated application is installed on the terminal.

[2000] 3. AI-OCR engine: A system that provides optical character recognition technology for extracting text information. A specific example of its use is the Google Cloud Vision API.

[2001] 4. NLP engine: An engine that uses natural language processing technology to improve the accuracy of extracted information. For example, spaCy is an example of this.

[2002] 5. Emotion Engine: An engine that recognizes user emotions and improves the operating experience, utilizing the Microsoft Emotion API.

[2003] System Operation Overview

[2004] The operation of the entire system will now be described in detail.

[2005] 1. Upload your documents

[2006] Users scan or photograph accounting documents and save them on their PC, smartphone, or other device, and then upload the documents to the server via the system's web interface or a dedicated app.

[2007] The terminal transmits a request to upload the selected file to the server.

[2008] 2. Receiving and sorting documents

[2009] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[2010] The server analyzes the stored files and automatically identifies their type, such as contract, invoice, purchase order, etc.

[2011] 3. Optical Character Recognition and Information Extraction

[2012] The server uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text information from the file.

[2013] The server receives the OCR processing results and temporarily stores the text data.

[2014] 4. Analysis of Information

[2015] The server analyzes the text data extracted from the OCR and identifies important information such as the contract number, contract date, amount, and business partner.

[2016] The server uses natural language processing (NLP) technology (e.g., spaCy) to accurately extract the required information and store it in the system's database.

[2017] 5. Clarifying accounting and tax issues

[2018] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[2019] 6. Accounting Proposal

[2020] The server looks up each company's specific chart of accounts and runs an algorithm to select the appropriate accounts.

[2021] The server displays the proposed account items on the user's operation screen so that the user can confirm and modify them.

[2022] 7. Document verification and entry

[2023] The server searches for relevant documents in the database, collates the information, and automatically enters the necessary transaction information (such as account, amount, and tax information).

[2024] 8. Send to accounting system

[2025] The server converts the final transaction information into the appropriate format and sends it to an external accounting system (e.g., SAP, QuickBooks).

[2026] The server checks whether the transmission was successful and notifies the user of the result.

[2027] 9. Emotion Engine Operation

[2028] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voices as the user operates the interface and recognize the user's emotional state.

[2029] The server dynamically adjusts the interface and feedback based on the user's emotional state. If the user is in a high stress state, the server suggests simplifying and automating the operation procedure.

[2030] Specific examples

[2031] Contract processing example

[2032] 1. The user scans the contract and saves it in PDF format on their device.

[2033] 2. The user activates the system's upload function and uploads the saved contract to the server.

[2034] 3. The device selects a file and sends an upload request to the server.

[2035] 4. The server receives the uploaded contract and stores it in temporary storage.

[2036] 5. The server automatically identifies the file as a contract and extracts the text data using an AI-OCR engine.

[2037] 6. The server analyzes the extracted data (contract number, contract date, amount, business partner, etc.) and stores it in a database.

[2038] 7. The server automatically determines whether consumption tax applies and the payment due date based on the stored data.

[2039] 8. The server references the company's chart of accounts and suggests appropriate accounts such as "sales" and "purchases."

[2040] 9. The user reviews the proposed accounts and modifies and approves them as necessary.

[2041] 10. The server compares the contents of the contract with other related documents and automatically enters the necessary information.

[2042] 11. The server converts the final transaction information into the appropriate format and sends it to the external accounting system.

[2043] 12. The server confirms the transmission was successful and notifies the user of the result.

[2044] 13. The server uses an emotion engine to analyze the user's emotional state and simplifies the interface if the stress level is high.

[2045] Example of input prompt for generative AI model

[2046] Please explain in natural language how the following system works: The system works as follows:

[2047] 1. The user uploads the accounting document to the terminal.

[2048] 2. The server receives the uploaded document, automatically identifies it, performs OCR processing, and extracts the text information.

[2049] 3. The server analyzes the extracted information and stores important information such as the contract number, contract date, amount, and business partner in a database.

[2050] 4. The server organizes accounting standards and tax issues based on the stored information and suggests appropriate account items.

[2051] 5. The user reviews the proposed accounts, makes any necessary corrections, and approves them.

[2052] 6. The server sends the information to the accounting system, confirms success, and notifies the user.

[2053] 7. The server analyzes the user's emotions using an emotion engine to optimize the operating experience.

[2054] Based on this, please explain the overall operation of the system and the specific program processing.

[2055] The above is a detailed description of the "Mode for Carrying Out the Invention."

[2056] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2057] Step 1:

[2058] Document upload

[2059] Users scan or photograph accounting documents, save them as PDF or image files on their devices, and then upload the documents to the server via the system's web interface or a dedicated app.

[2060] Input: Accounting document file (PDF or image file)

[2061] Output: Upload request to server

[2062] Specific operation: The user opens the file selection dialog, selects an accounting document file, and presses the "Upload" button.

[2063] Step 2:

[2064] Receiving and temporarily storing documents

[2065] The server receives the file sent from the device, stores it in a temporary storage area, and records the metadata of the received file (upload date and time, user ID, file format, etc.).

[2066] Input: Uploaded accounting document file

[2067] Output: Files and their metadata stored in temporary storage

[2068] Specific operation: The server saves the received file in storage and records the metadata in the database.

[2069] Step 3:

[2070] Document sorting

[2071] The server analyzes the stored files and automatically identifies the type of document, such as a contract, invoice, or purchase order.

[2072] Input: A file saved in temporary storage

[2073] Output: Identified document type metadata

[2074] How it works: The server checks the file contents and determines the document type based on a pre-trained model.

[2075] Step 4:

[2076] Optical character recognition (OCR)

[2077] The server extracts text information from the file using an AI-OCR engine (e.g., Google Cloud Vision API).

[2078] Input: Identified accounting document file

[2079] Output: Extracted character information (text data)

[2080] Specific operation: The server sends the file to the AI-OCR engine and obtains the character information.

[2081] Step 5:

[2082] Analysis of information

[2083] The server analyzes the text data extracted from the OCR and extracts important information such as the contract number, contract date, amount, and business partner.

[2084] Input: Text data extracted from OCR

[2085] Output: Extracted important information (contract number, contract date, amount, business partner, etc.)

[2086] Specific operation: The server analyzes the text data using natural language processing (NLP) technology (e.g., spaCy) and extracts the necessary information.

[2087] Step 6:

[2088] Clarifying accounting and tax issues

[2089] The server organizes accounting standards and tax issues based on the stored information, and automatically determines whether consumption tax applies and the payment deadline.

[2090] Input: Sensitive information stored in the database

[2091] Output: Organized accounting and tax information

[2092] Specific operation: The server automatically determines whether consumption tax applies, the payment due date, etc. in accordance with accounting standards and tax regulations.

[2093] Step 7:

[2094] Account suggestion

[2095] The server refers to the chart of accounts set for each company and selects the most appropriate account.

[2096] Input: Organized accounting and tax information

[2097] Output: Proposed accounts

[2098] How it works: The server runs an algorithm to suggest appropriate accounts from each company's chart of accounts.

[2099] Step 8:

[2100] Account suggestion and adjustment

[2101] The server displays the proposed account items on the user's operation screen.

[2102] The user reviews the proposed accounts and makes any necessary corrections.

[2103] Input: Proposed Account

[2104] Output: Accounts confirmed and modified by the user

[2105] Specific behavior: The user reviews the proposed accounts on the screen, makes any necessary corrections, and finally approves them.

[2106] Step 9:

[2107] Document verification and entry

[2108] The server retrieves relevant documents from a database and collates the information.

[2109] The server automatically enters the necessary information (subject, amount, tax information, etc.) based on the matching results.

[2110] Input: Related documents and accounts modified and approved by the user

[2111] Output: Auto-filled transaction information

[2112] How it works: The server searches for relevant documents in a database, collates the information, and automatically fills in the necessary transaction information.

[2113] Step 10:

[2114] Send to accounting system

[2115] The server converts the final transaction information into the appropriate format while maintaining consistency and transmits it to the external accounting system.

[2116] The server checks whether the transmission was successful and notifies the user of the result.

[2117] Input: Auto-filled transaction information

[2118] Output: Transaction information sent to an external accounting system and notification of the sending result

[2119] Specific operations: The server converts the transaction information into an appropriate format, sends the data to the external accounting system, confirms the success of the transmission, and notifies the user.

[2120] Step 11:

[2121] Emotion Engine Operation

[2122] The server uses an emotion engine (e.g., Microsoft Emotion API) to analyze facial expressions and voice as the user interacts with the interface and recognize the user's emotional state.

[2123] The server dynamically adjusts the interface and feedback based on the perceived emotional state.

[2124] Input: User's facial expressions and voice data

[2125] Output: Dynamically adjusted interface and feedback

[2126] Specific operation: The server uses the emotion engine to monitor the user's emotional state and adjust the interface and feedback.

[2127] The above is the flow of processing of the program of this system.

[2128] (Application example 2)

[2129] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a...

Claims

1. means for receiving documents; means for extracting textual information using optical character recognition technology; A means of analyzing the extracted information and making decisions based on multiple accounting standards and taxation; A means to refer to the account items set for each company and suggest appropriate account items, A means for presenting the proposed account items to the user and allowing the user to confirm and modify them; A means of matching relevant documents and automatically inputting transaction information; a means for transmitting the consolidated transaction information to an external accounting system; means for notifying the user of the transmission result; A system including:

2. 10. The system of claim 1, further comprising means for automatically identifying the document type and selecting the appropriate processing procedure.

3. The system of claim 1 , further comprising means for improving the accuracy of the extracted information using natural language processing techniques.

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