Semantic Tree Translation With Phrase Bank Verification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing machine translation systems lack accuracy and reliability for critical translations, particularly in healthcare and other industries where precise communication is essential, leading to potential misinterpretation and serious consequences.
Innovation Solution
A computer-implemented method that identifies portions of input text to be replaced with semantic structures, organizes them into a semantic tree, and matches them to a verified phrase bank for near real-time translation, allowing users to verify the accuracy of the translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If statistical machine translation programs are used for quick translation output, then translation speed is improved, but translation accuracy and reliability deteriorate
Solution Approach 1:
The patent segments the translation process into multiple independent components: statistical machine translation for rapid draft generation, semantic structure extraction for meaning preservation, phrase bank matching for verified terminology, and back-translation for accuracy verification. This segmentation allows each component to specialize, maintaining speed while improving reliability through layered processing.
Solution Approach 2:
The system implements feedback loops where translation outputs are back-translated to the source language for verification, and where semantic structures are matched against a verified phrase bank. This feedback mechanism allows the system to detect and correct errors, ensuring translation accuracy without sacrificing the speed benefits of statistical machine translation.
2Reliability
If multiple professional linguists perform forward translation, editing, back translation, and reconciliation, then translation accuracy is improved, but translation speed deteriorates
Solution Approach 1:
The system enables self-service translation verification through automated back-translation and semantic structure matching. The translation system performs its own quality control by comparing outputs against the verified phrase bank and generating back-translations for validation, eliminating the need for multiple human linguists while maintaining high accuracy standards.
Solution Approach 2:
The patent replaces the mechanical process of multiple human linguists performing sequential translation tasks with an automated computational system. The system uses algorithms for semantic structure extraction, phrase bank matching, and back-translation verification to automate what previously required manual intervention by multiple professionals, thereby maintaining accuracy while dramatically improving speed.
3Ease of operation
If online translators are used to provide quick translation output, then ease of use and speed are improved, but context understanding and accuracy deteriorate
Solution Approach 1:
The system performs preliminary action by pre-building a verified phrase bank containing contextually accurate translations and semantic structures before the actual translation task. This pre-prepared knowledge base allows the system to quickly match and retrieve accurate translations with proper context understanding, maintaining both ease of use and reliability without requiring complex real-time analysis.
Data Source
AI summary
A computer-implemented method is provided for translating input text from a source language to a target language including receiving, by an interface, the input text in a source language, and identifying, by a processor coupled to the interface, at least one portion of the input text. The method includes replacing each portion with a corresponding sematic structure to produce at least one semantic structure, and organizing the at least one semantic structure into a semantic tree. The method includes matching a portion of the semantic tree to at least one phrase from a stored phrase bank, and providing one or more versions of the at least one phrase in the source language. The method includes receiving a selected version of the set of versions, translating the selected version from the source language to the target language, and providing the selected version in the target language.