A machine-assisted human translation system for technical documents

Translation systems are known to benefit from the availability of a bilingual lexicon for a domain of interest. A system, aiming to build such a lexicon from source language corpus, often requires human assistance and is confronted by conflicting requirements of minimizing human translation effort while improving the translation quality. We present an approach that exploits redundancy in the source corpus and extracts recurring patterns which are: frequent, syntactically well-formed, and provide maximum corpus coverage. The patterns generalize over phrases and word types and our approach finds a succinct set of good patterns with high coverage. Our interactive system leverages these patterns in multiple iterations of translation and post-editing, thereby progressively generating a high quality bilingual lexicon.

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