Paper: Grammar Comparison Study for Translational Equivalence Modeling and Statistical Machine Translation

ACL ID C08-1138
Title Grammar Comparison Study for Translational Equivalence Modeling and Statistical Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

This paper presents a general platform, namely synchronous tree sequence sub- stitution grammar (STSSG), for the grammar comparison study in Transla- tional Equivalence Modeling (TEM) and Statistical Machine Translation (SMT). Under the STSSG platform, we compare the expressive abilities of various gram- mars through synchronous parsing and a real translation platform on a variety of Chinese-English bilingual corpora. Ex- perimental results show that the STSSG is able to better explain the data in paral- lel corpora than other grammars. Our study further finds that the complexity of structure divergence is much higher than suggested in literature, which imposes a big challenge to syntactic transformation- based SMT.