Mistranslation Detection Index Using Search Engine Verification
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Solution Overview
Problem
Machine translation often produces grammatically correct but contextually unsuitable terms, particularly for specific fields, due to its inability to infer context, leading to inefficiencies in detecting and correcting mistranslations.
Innovation Solution
A method that uses internet searches to evaluate the suitability of translated words by analyzing the number of matching pages at specific and all sites, generating an index to indicate the probability of mistranslation, and presenting this information to users to quickly detect and improve translation quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If machine translation is used to translate information, then the translation speed and productivity are improved, but the accuracy and reliability of translation deteriorate due to inability to infer context
Solution Approach 1:
The patent introduces an intermediary verification system that uses search engines to check translated words against the original text and context. The search engine acts as a mediator to validate whether the translated word appears in the source document or related contexts, thereby improving translation reliability without significantly reducing productivity
Solution Approach 2:
The system implements feedback mechanisms where translation results are automatically verified by searching for the translated words in the original document and related documents. This feedback loop identifies potential mistranslations by checking if the translated word appears in the source text or if the search returns unexpected results, allowing for automatic or semi-automatic correction
2Reliability
If manual checking is performed to verify translation accuracy, then the reliability of translation is improved, but the time consumption and productivity loss increase significantly
Solution Approach 1:
The system enables self-service verification where the translation system automatically checks its own output using search engines. The translated words are searched against the original document and related documents to verify accuracy, eliminating the need for extensive manual checking while maintaining high reliability
Solution Approach 2:
The patent replaces the mechanical manual checking process with an automated electronic verification system using search engines. This substitution transforms the manual verification task into an automated information retrieval and analysis process, dramatically reducing time consumption while maintaining or improving verification quality
3Measurement precision
If search verification is performed for each translated word, then the detection precision of mistranslation is improved, but the processing time and productivity are reduced
Solution Approach 1:
The system applies partial verification by focusing search checks on specific translated words that are more likely to be mistranslations, such as technical terms, proper nouns, or words with multiple possible translations. This selective approach maintains high detection precision while reducing the overall processing burden compared to verifying every single word
Solution Approach 2:
The system performs preliminary actions by pre-processing the original document to identify key terms, technical vocabulary, and potential translation candidates before the actual translation and verification process. This preliminary analysis enables more efficient targeted verification, improving both precision and processing speed
Data Source
AI summary
Methods and apparatus, including computer program products, for providing assistance in detecting mistranslation in a translated document obtained by performing machine translation of an original document. A word included in the translated document is obtained. Search results are obtained of searching both a first document data group and a second document data group including the first document data group for pieces of document data related to the obtained word. Based on the obtained search results, an index is generated. The index indicates the adequacy of the obtained word as a translated word in a field corresponding to the first document data group. The generated index is output.