Multi-language version automatic generation and synchronization system of international trade document

Abstract

The invention relates to the technical field of natural language processing, in particular to a multi-language version automatic generation and synchronization system for international trade documents. Comprising a document processing unit, an intelligent translation unit, a version synchronization unit and a collaborative review unit. A term library is updated in real time, the multiplexing value of a translation memory library is optimized, an advanced deep learning mechanism and strict quality control are applied, high-quality translation results closely following industry dynamics are output, meanwhile, a version synchronization unit saves resources by means of monitoring source document changes in real time and incremental translation, and updating records are safely stored by means of the block chain technology; automatic generation and real-time synchronization of the multi-language document are achieved, the document quality, safety and compliance are guaranteed, and the accuracy, efficiency and collaboration of international trade document processing are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of natural language processing, and in particular to a system for automatically generating and synchronizing multilingual versions of international trade documents. Background Art

[0002] Amidst the surging tide of globalization, international trade activities are becoming increasingly frequent and in-depth. As businesses expand their cross-border businesses, they must process massive volumes of international trade documents, such as contracts, bills of lading, and invoices. These documents often face the challenge of multilingual translation. Traditional manual translation is not only inefficient and unable to keep up with the rapid pace of business, but is also prone to inconsistent terminology and inaccurate translations, seriously impacting the smooth flow of trade communication and the security of transactions. Furthermore, differences in document formats and data standards across countries and regions further complicate document processing. Furthermore, with the dynamic development of business, document content is constantly updated. Ensuring real-time synchronization of multiple language versions and maintaining consistency across them has become a pressing pain point for businesses. While existing technologies offer some auxiliary means, they still struggle to meet the complex and ever-changing demands of international trade in terms of automation, translation quality control, and timely version synchronization. Therefore, the development of an accurate and efficient system for automatically generating and synchronizing multiple language versions of international trade documents is imperative. In the existing technology, the system often has problems such as insufficient translation accuracy, delayed terminology updates, low translation efficiency, asynchronous multilingual document versions, poor data security and traceability, and poor document processing collaboration.

[0003] Based on this, the present invention provides a system for automatically generating and synchronizing multi-language versions of international trade documents to solve the above-mentioned technical problems. Summary of the Invention

[0004] The purpose of the present invention is to provide a system for automatically generating and synchronizing multilingual versions of international trade documents. The present invention outputs high-quality translation results that keep up with industry trends by updating the terminology library in real time, optimizing the reuse value of the translation memory library, applying advanced deep learning mechanisms and strict quality control. At the same time, the version synchronization unit relies on real-time monitoring of source document changes, incremental translation to save resources, and blockchain technology to securely store update records, thereby realizing the automatic generation and real-time synchronization of multilingual documents, ensuring document quality, security and compliance, and improving the accuracy, efficiency and coordination of international trade document processing.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The present invention provides a system for automatically generating and synchronizing multilingual versions of international trade documents, including a document processing unit, an intelligent translation unit, a version synchronization unit, and a collaborative review unit, wherein:

[0007] The document processing unit is used to automatically parse and extract structured content from documents, completely retain the original format, and provide standardized input for multilingual conversion;

[0008] The intelligent translation unit: based on a dynamically updated professional terminology database and translation memory, achieves context-sensitive and precise semantic conversion through deep learning algorithms;

[0009] The version synchronization unit is used to achieve real-time synchronization and tamper-proof verification of multi-language versions through an incremental translation engine and blockchain distributed ledger technology;

[0010] The collaborative review unit is used to establish a cross-language, cross-regional multi-role collaborative workflow, supporting full life cycle management from content review, annotation revision to electronic signature.

[0011] The original format includes information on font, font size, paragraph format, table structure, and image position.

[0012] The document processing unit includes a document parsing module, a content extraction module, a format retention module, and a standardized output module, wherein:

[0013] The document parsing module is used to identify the format and analyze the content structure of various international trade documents;

[0014] The content extraction module is used to accurately extract structured text content from the parsed document;

[0015] The format retention module is used to record and save the original format information of the document to ensure that the format is consistent when multiple language versions are generated;

[0016] The standardized output module is used to organize the extracted content and format information into standardized input according to system specifications.

[0017] The intelligent translation unit includes a terminology management module, a translation memory optimization module, a deep learning translation module, and a quality assessment module, wherein:

[0018] The terminology database management module is used to crawl the terminology changes published by the WTO and ICC authorities in real time through a crawler, and update the professional terminology database in real time;

[0019] The translation memory optimization module is used to automatically evaluate the reuse value of translation memory using reinforcement learning;

[0020] The deep learning translation module is used to use deep learning algorithms and combine context information to perform accurate semantic conversion;

[0021] The quality assessment module is used to perform quality detection and assessment on the translation results to ensure that the translation quality meets the standards.

[0022] The reinforcement learning in the translation memory optimization module adopts an objective function including a clipping mechanism:

[0023]

[0024] Among them, ∈ is the preset clipping threshold; π θ is the current policy network, A t is the advantage function;

[0025] The immediate reward function is:

[0026] r t =ɑ·Sim(m t ,q t )+β·UserCorr(m t )-λ·Age(m t )

[0027] Where Sim(·) represents the similarity between the memory segment and the text to be translated; UserCorr(·) reflects the user's correction history; and Age(·) is the time decay factor.

[0028] The deep learning algorithm in the deep learning translation module adopts a multi-head attention mechanism, and its calculation formula process is as follows:

[0029]

[0030] Among them, Q, K, V represent the query matrix, key matrix and value matrix respectively; d k is the dimension of the key vector;

[0031] Multi-head output is passed through the weight matrix W O To splice:

[0032] MultiHead(Q,K,V)=Concat(head1,…,head h )W O

[0033] The calculation of each attention head satisfies:

[0034]

[0035] in, Represents the head-specific parameter matrix.

[0036] The version synchronization unit includes a change monitoring module, an incremental translation module, a blockchain storage module, and a synchronization update module, wherein:

[0037] The change monitoring module is used to monitor changes in source documents in real time;

[0038] The incremental translation module is used to translate only the changed parts of the source document;

[0039] The blockchain storage module is used to securely store update records of multilingual versions using blockchain technology;

[0040] The synchronization update module is used to synchronize the translation update content to each language version.

[0041] The blockchain storage module is used to securely store update records of multilingual versions using blockchain technology. The specific operations are as follows:

[0042] A1: Select a blockchain platform based on system requirements, deploy nodes, and properly configure network parameters to build a blockchain network;

[0043] A2: Based on the collected update records, encoding and calculating hash values ​​complete preprocessing;

[0044] A3: Design smart contracts covering storage, permissions, and verification functions and deploy them to the blockchain network;

[0045] A4: The updated record hash value is encapsulated into a transaction broadcast, which is then stored on the blockchain by the smart contract after consensus.

[0046] A5: Develop a query interface for authorized users to query, use hash values ​​to verify data, and implement audit traceability;

[0047] A6: Use encryption, set access controls, and anonymize sensitive information to ensure security and privacy.

[0048] The network parameters include consensus algorithm, block size, and block time.

[0049] The collaborative review unit includes a workflow building module, a content review module, an annotation revision module, and an electronic signature module, wherein:

[0050] The workflow building module is used to build a cross-language, cross-regional multi-role collaborative workflow and standardize the review process;

[0051] The content review module is used to provide document review tools to facilitate reviewers to view and check content;

[0052] The annotation revision module is used to support reviewers in adding annotations and making revision suggestions;

[0053] The electronic signature module is used to implement electronic signature operations that comply with regulatory requirements and complete the full life cycle management of documents.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention outputs high-quality translation results that keep up with industry trends by updating the terminology library in real time, optimizing the reuse value of the translation memory, applying advanced deep learning mechanisms and strict quality control. At the same time, the version synchronization unit relies on real-time monitoring of source document changes, incremental translation to save resources, and blockchain technology to securely store update records, thereby realizing automatic generation and real-time synchronization of multilingual documents, ensuring document quality, security and compliance, and improving the accuracy, efficiency and coordination of international trade document processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A system diagram of the system for automatically generating and synchronizing multiple language versions of international trade documents according to the present invention.

[0057] Figure 2 A system diagram of a document processing unit in a system for automatically generating and synchronizing multilingual versions of international trade documents according to the present invention.

[0058] Figure 3 A system diagram of an intelligent translation unit in the system for automatically generating and synchronizing multiple language versions of international trade documents according to the present invention.

[0059] Figure 4 A system diagram of a version synchronization unit in the system for automatically generating and synchronizing multiple language versions of international trade documents according to the present invention.

[0060] Figure 5 A system diagram of a collaborative review unit in the system for automatically generating and synchronizing multilingual versions of international trade documents according to the present invention.

[0061] Description of Figure Numbers:

[0062] 100. Document processing unit; 101. Document parsing module; 102. Content extraction module; 103. Format retention module; 104. Standardized output module; 200. Intelligent translation unit; 201. Term base management module; 202. Translation memory optimization module; 203. Deep learning translation module; 204. Quality assessment module; 300. Version synchronization unit; 301. Change monitoring module; 302. Incremental translation module; 303. Blockchain storage module; 304. Synchronous update module; 400. Collaborative review unit; 401. Workflow construction module; 402. Content review module; 403. Annotation and revision module; 404. Electronic signature module. DETAILED DESCRIPTION

[0063] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0064] Example:

[0065] like Figure 1-Figure 5 As shown, this embodiment provides a system for automatically generating and synchronizing multilingual versions of international trade documents, including a document processing unit 100, an intelligent translation unit 200, a version synchronization unit 300, and a collaborative review unit 400, wherein:

[0066] Document processing unit 100: used to automatically parse and extract structured content from documents, fully retaining the original format, and provide standardized input for multilingual conversion;

[0067] Intelligent Translation Unit 200: Based on a dynamically updated professional terminology database and translation memory, it uses deep learning algorithms to achieve context-sensitive and precise semantic conversion;

[0068] Version synchronization unit 300: used to achieve real-time synchronization and tamper-proof verification of multi-language versions through an incremental translation engine and blockchain distributed ledger technology;

[0069] Collaborative Review Unit 400: Used to establish cross-language and cross-regional multi-role collaborative workflows, supporting full lifecycle management from content review, annotation revision to electronic signature.

[0070] The original format includes information about font, font size, paragraph format, table structure, and image position.

[0071] The document processing unit 100 includes a document parsing module 101, a content extraction module 102, a format retention module 103, and a standardized output module 104, wherein:

[0072] The document parsing module 101 is used to identify the format and analyze the content structure of various international trade documents;

[0073] The content extraction module 102 is used to accurately extract structured text content from the parsed document;

[0074] The format retention module 103 is used to record and save the original format information of the document to ensure that the format is consistent when multiple language versions are generated;

[0075] The standardized output module 104 is used to organize the extracted content and format information into standardized input according to system specifications.

[0076] The intelligent translation unit 200 includes a terminology library management module 201, a translation memory library optimization module 202, a deep learning translation module 203, and a quality assessment module 204, wherein:

[0077] The terminology database management module 201 is used to crawl the terminology changes published by the WTO and ICC authorities in real time through a crawler, and update the professional terminology database in real time;

[0078] The translation memory optimization module 202 is used to automatically evaluate the reuse value of translation memory using reinforcement learning;

[0079] The deep learning translation module 203 is used to use deep learning algorithms and combine context information to perform accurate semantic conversion;

[0080] The quality assessment module 204 is used to perform quality detection and assessment on the translation results to ensure that the translation quality meets the standards.

[0081] The reinforcement learning in the translation memory optimization module 202 adopts an objective function including a clipping mechanism:

[0082]

[0083] Among them, ∈ is the preset clipping threshold; π θ is the current policy network, A t is the advantage function;

[0084] The immediate reward function is:

[0085] r t =α·Sim(m t ,q t )+β·UserCorr(m t )-λ·Age(m t )

[0086] Where Sim(·) represents the similarity between the memory segment and the text to be translated; UserCorr(·) reflects the user's correction history; and Age(·) is the time decay factor.

[0087] The deep learning algorithm in the deep learning translation module 203 adopts a multi-head attention mechanism, and its calculation formula process is:

[0088]

[0089] Among them, Q, K, V represent the query matrix, key matrix and value matrix respectively; d k is the dimension of the key vector;

[0090] Multi-head output is passed through the weight matrix W O To splice:

[0091] MultiHead(Q,K,V)=Concat(head1,…,head h )W O

[0092] The calculation of each attention head satisfies:

[0093]

[0094] in, Represents the head-specific parameter matrix.

[0095] The version synchronization unit 300 includes a change monitoring module 301, an incremental translation module 302, a blockchain storage module 303, and a synchronization update module 304, wherein:

[0096] The change monitoring module 301 is used to monitor changes in source documents in real time;

[0097] The incremental translation module 302 is used to translate only the changed parts of the source document;

[0098] The blockchain storage module 303 is used to securely store update records of multilingual versions using blockchain technology;

[0099] The synchronization update module 304 is used to synchronize the translation update content to each language version.

[0100] The blockchain storage module 303 is used to securely store update records of the multilingual version using blockchain technology. The specific operations are as follows:

[0101] A1: Select a blockchain platform based on system requirements, deploy nodes, and properly configure network parameters to build a blockchain network;

[0102] A2: Based on the collected update records, encoding and calculating hash values ​​complete preprocessing;

[0103] A3: Design smart contracts covering storage, permissions, and verification functions and deploy them to the blockchain network;

[0104] A4: The updated record hash value is encapsulated into a transaction broadcast, which is then stored on the blockchain by the smart contract after consensus.

[0105] A5: Develop a query interface for authorized users to query, use hash values ​​to verify data, and implement audit traceability;

[0106] A6: Use encryption, set access controls, and anonymize sensitive information to ensure security and privacy.

[0107] Network parameters such as consensus algorithm, block size, and block time.

[0108] The collaborative review unit 400 includes a workflow building module 401, a content review module 402, an annotation and revision module 403, and an electronic signature module 404, wherein:

[0109] The workflow building module 401 is used to build a cross-language, cross-regional multi-role collaborative workflow and standardize the review process;

[0110] The content review module 402 is used to provide document review tools to facilitate reviewers to view and check the content;

[0111] The annotation and revision module 403 is used to support reviewers in adding annotations and making revision suggestions;

[0112] The electronic signature module 404 is used to implement electronic signature operations that comply with regulatory requirements and complete the full life cycle management of documents.

[0113] like Figure 1-Figure 5 It is shown that this embodiment provides a multi-language version automatic generation and synchronization system for international trade documents, and the specific method is as follows: First, the document parsing module 101 is used to perform format recognition and content structure analysis on various types of international trade documents; a CNN+RNN hybrid architecture is adopted, in which CNN processes image features and RNN processes text sequence features. The content extraction module 102 is used to accurately extract structured text content from the parsed document; the format retention module 103 is used to record and save the original format information of the document to ensure that the format is consistent when multi-language versions are generated; the standardized output module 104 is used to organize the extracted content and format information into standardized input according to system specifications. Secondly, the terminology library management module 201 is used to crawl the terminology changes issued by the authoritative organizations of WTO and ICC in real time through crawlers, and update the professional terminology library in real time; the translation memory library optimization module 202 is used to automatically evaluate the reuse value of translation memory using reinforcement learning; reinforcement learning adopts an objective function that includes a clipping mechanism:

[0114]

[0115] Among them, ∈ is the preset clipping threshold; π θ is the current policy network, A t is the advantage function;

[0116] The immediate reward function is:

[0117] r t =ɑ·Sim(m t ,q t )+β·UserCorr(m t )-λ·Age(m t )

[0118] Where Sim(·) represents the similarity between the memory segment and the text to be translated; UserCorr(·) reflects the user's correction history; and Age(·) is the time decay factor. The deep learning translation module 203 is used to apply a deep learning algorithm to perform accurate semantic conversion in combination with contextual information. The deep learning algorithm uses a multi-head attention mechanism, and its calculation formula is as follows:

[0119]

[0120] Among them, Q, K, V represent the query matrix, key matrix and value matrix respectively; d k is the dimension of the key vector;

[0121] Multi-head output is passed through the weight matrix W O To splice:

[0122] MultiHead(Q,K,V)=Concat(head1,…,head h )W O

[0123] The calculation of each attention head satisfies:

[0124]

[0125] in, The header's exclusive parameter matrix. The quality assessment module 204 performs quality inspection and evaluation on translation results to ensure that translation quality meets standards. The change monitoring module 301 monitors changes to the source document in real time. The incremental translation module 302 translates only the modified portions of the source document. The blockchain storage module 303 securely stores update records for multiple language versions using blockchain technology. The specific operations are as follows: A1: Select a blockchain platform based on system requirements, deploy nodes, and appropriately configure network parameters to build a blockchain network. The blockchain platform can be a consortium blockchain or a public blockchain. Network parameters include consensus algorithm, block size, and block time. A2: Based on the collected update records, encode and calculate hash values ​​to complete preprocessing. A3: Design a smart contract with storage, permissions, and verification functions and deploy it to the blockchain network. A4: Encapsulate the update record hash value into a transaction broadcast. After consensus, the smart contract stores it on the blockchain. The storage format may be JSON or binary. A5: Develop a query interface for authorized users to query, using hash values ​​to verify data and implement audit traceability. Hash values ​​can be used to verify the integrity and authenticity of update records. A6: Security and privacy are ensured through the use of encryption, access control, and the anonymization of sensitive information. The Synchronous Update Module 304 synchronizes translation updates across all language versions. Finally, the Workflow Construction Module 401 establishes a multi-role collaborative workflow across languages ​​and regions, standardizing the review process. The Content Review Module 402 provides document review tools to facilitate reviewers in viewing and checking content. The Annotation and Revision Module 403 supports reviewers in adding annotations and suggesting revisions. The Electronic Signature Module 404 implements electronic signatures that comply with regulatory requirements, completing the full lifecycle management of documents.

[0126] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0127] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The system for automatically generating and synchronizing multilingual versions of international trade documents is characterized by: The system comprises a document processing unit (100), an intelligent translation unit (200), a version synchronization unit (300), and a collaborative review unit (400), wherein: The document processing unit (100) is used to automatically parse and extract structured content in the document, completely retain the original format, and provide standardized input for multi-language conversion; The intelligent translation unit (200) is based on a dynamically updated professional terminology database and translation memory database, and realizes context-related precise semantic conversion through a deep learning algorithm; The version synchronization unit (300) is used to achieve real-time synchronization update and tamper-proof verification of multi-language versions through an incremental translation engine and blockchain distributed ledger technology; The collaborative review unit (400) is used to establish a cross-language, cross-regional multi-role collaborative workflow, supporting full life cycle management from content review, annotation revision to electronic signature.

2. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 1, characterized in that: The original format includes information on font, font size, paragraph format, table structure, and image position.

3. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 2, characterized in that: The document processing unit (100) comprises a document parsing module (101), a content extraction module (102), a format retention module (103), and a standardized output module (104), wherein: The document parsing module (101) is used to perform format recognition and content structure analysis on various international trade documents; The content extraction module (102) is used to accurately extract structured text content from the parsed document; The format retention module (103) is used to record and save the original format information of the document to ensure that the format is consistent when multiple language versions are generated; The standardized output module (104) is used to organize the extracted content and format information into standardized input according to system specifications.

4. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 1, characterized in that: The intelligent translation unit (200) includes a terminology library management module (201), a translation memory library optimization module (202), a deep learning translation module (203), and a quality assessment module (204), wherein: The terminology database management module (201) is used to crawl terminology changes published by authoritative organizations such as the WTO and the ICC in real time through a crawler, and update the professional terminology database in real time; The translation memory optimization module (202) is used to automatically evaluate the reuse value of translation memory using reinforcement learning; The deep learning translation module (203) is used to use a deep learning algorithm to perform accurate semantic conversion in combination with context information; The quality assessment module (204) is used to perform quality detection and assessment on the translation results to ensure that the translation quality meets the standards.

5. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 4, characterized in that: The reinforcement learning in the translation memory optimization module (202) adopts an objective function including a clipping mechanism: Among them, ∈ is the preset clipping threshold; π θ is the current policy network, A t is the advantage function; The immediate reward function is: r t =α·Sim(m t ,q t )+β·UserCorr(m t )-λ·Age(m t ) Where Sim(·) represents the similarity between the memory segment and the text to be translated; UserCorr(·) reflects the user's correction history; and Age(·) is the time decay factor.

6. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 5, characterized in that: The deep learning algorithm in the deep learning translation module (203) adopts a multi-head attention mechanism, and its calculation formula process is: Among them, Q, K, V represent the query matrix, key matrix and value matrix respectively; d k is the dimension of the key vector; Multi-head output is passed through the weight matrix W O To splice: MultiHead(Q,K,V)=Concat(head1,…,head h )W O The calculation of each attention head satisfies: in, Represents the head-specific parameter matrix.

7. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 1, characterized in that: The version synchronization unit (300) includes a change monitoring module (301), an incremental translation module (302), a blockchain storage module (303), and a synchronization update module (304), wherein: The change monitoring module (301) is used to monitor changes in source documents in real time; The incremental translation module (302) is used to translate only the changed part of the source document; The blockchain storage module (303) is used to securely store update records of multiple language versions using blockchain technology; The synchronization update module (304) is used to synchronize the translation update content to each language version.

8. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 7, characterized in that: The blockchain storage module (303) is used to securely store the update records of the multi-language version using blockchain technology, and the specific operations are as follows: A1: Select a blockchain platform based on system requirements, deploy nodes, and properly configure network parameters to build a blockchain network; A2: Based on the collected update records, encoding and calculating hash values ​​complete preprocessing; A3: Design smart contracts covering storage, permissions, and verification functions and deploy them to the blockchain network; A4: The updated record hash value is encapsulated into a transaction broadcast, which is then stored on the blockchain by the smart contract after consensus. A5: Develop a query interface for authorized users to query, use hash values ​​to verify data, and implement audit traceability; A6: Use encryption, set access controls, and anonymize sensitive information to ensure security and privacy.

9. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 8, characterized in that: The network parameters include consensus algorithm, block size, and block time.

10. The system for automatically generating and synchronizing multilingual versions of international trade documents according to claim 1, characterized in that: The collaborative review unit (400) includes a workflow building module (401), a content review module (402), an annotation and revision module (403), and an electronic signature module (404), wherein: The workflow building module (401) is used to build a cross-language, cross-regional multi-role collaborative workflow and standardize the review process; The content review module (402) is used to provide a document review tool to facilitate reviewers to view and check the content; The annotation revision module (403) is used to support reviewers in adding annotations and making revision suggestions; The electronic signature module (404) is used to implement electronic signature operations that comply with regulatory requirements and complete the full life cycle management of documents.

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