Using supertags as source language context in SMT
Haque, Rejwanul and Naskar, Sudip Kumar and Ma, Yanjun and Way, Andy (2009) Using supertags as source language context in SMT. In: EAMT 2009 - 13th Annual Conference of the European Association for Machine Translation, 13-15 May 2009, Barcelona, Spain.
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Recent research has shown that Phrase-Based Statistical Machine Translation (PB-SMT) systems can benefit from two
enhancements: (i) using words and POS tags as context-informed features on the source side; and (ii) incorporating lexical syntactic descriptions in the form of supertags on the target side. In this work we
present a novel PB-SMT model that combines these two aspects by using supertags as source language contextinformed features. These features enable us to exploit source similarity in addition to target similarity, as modelled by the language model. In our experiments two
kinds of supertags are employed: those from Lexicalized Tree-Adjoining Grammar and Combinatory Categorial Grammar.
We use a memory-based classification framework that enables the estimation of these features while avoiding
problems of sparseness. Despite the differences between these two approaches, the supertaggers give similar improvements. We evaluate the performance of our approach on an English-to-Chinese translation task using a state-of-the-art phrase-based SMT system, and report an
improvement of 7.88% BLEU score in translation quality when adding supertags as context-informed features.
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