Semantic Cohesion Model for Phrase-Based SMT
Minwei Feng, Weiwei Sun · RWTH Publications (RWTH Aachen) · 2012
In this paper, we propose a novel semantic cohesion model.Our model utilizes the predicateargument structures as soft constraints and plays the role as a reordering model in the phrasebased statistical machine translation system.We build a translation system with GALE data.Experimental results on the NIST02, NIST03, NIST04, NIST05 and NIST08 Chinese-English tasks show that our model improves the baseline system by 0.93 BLEU 0.98 TER on average.We also compare our method with a syntax-augmented model (Cherry, 2008), and demonstrate the importance of predicate-argument semantics in machine translation.