Translation Memories (TM) help translators in their task by retrieving previously translated sentences and editing fuzzy matches when no exact match is found by the system. Current TM systems use simple edit-distance or some variation of it, which largely relies on the surface form of the sentences and does not necessarily reflect the semantic similarity of segments as judged by humans. In this paper, we propose an intelligent metric to compute the fuzzy match score, which is inspired by similarity and entailment techniques developed in Natural Language Processing.
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