Maximum Entropy Based Lexical Reordering Model for Hierarchical Phrase-based Machine Translation
Zhongguang Zheng, Yao Meng, Hao Yu · Institutional Repositories DataBase (IRDB) · 2011
Abstract. The hierarchical phrase-based (HPB) model on the basis of a synchronous context-free grammar (SCFG) is prominent in solving global reorderings. However, the HPB model is inadequate to supervise the reordering process so that sometimes positions of dif-ferent lexicons are switched due to the incorrect SCFG rules. In this paper, we consider the order of two lexicons as a classification problem and propose a novel lexical reorder-ing model based on a maximum entropy classifier. Our model employs the word alignment and translation during the decoding process. Experimental results on the Chinese-to-English task showed that our method outperformed the baseline system in BLEU score significantly. Moreover, the translation results further proved the effectiveness of our approach.