A Discriminative Latent Variable-Based "DE" Classifier for Chinese-English SMT
Jinhua Du, Andy Way · 2010
Syntactic reordering on the source-side is an effective way of handling word order differences. The d (DE) construction is a flexible and ubiquitous syntactic structure in Chinese which is a major source of error in translation quality. In this paper, we propose a new classifier model — discriminative latent variable model (DPLVM) — to classify the DE construction to improve the accuracy of the classification and hence the translation quality. We also propose a new feature which can automatically learn the reordering rules to a certain extent. The experimental results show that the MT systems using the data reordered by our proposed model outperform the baseline systems by 6.42 % and 3.08 % relative points in terms of the BLEU score on PB-SMT and hierarchical phrase-based MT respectively. In addition, we analyse the impact of DE annotation on word alignment and on the SMT phrase table. 1