Paper: Sentence Type Based Reordering Model for Statistical Machine Translation

ACL ID C08-1137
Title Sentence Type Based Reordering Model for Statistical Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

Many reordering approaches have been proposed for the statistical machine translation (SMT) system. However, the information about the type of source sentence is ignored in the previous works. In this paper, we propose a group of novel reordering models based on the source sentence type for Chinese-to- English translation. In our approach, an SVM-based classifier is employed to classify the given Chinese sentences into three types: special interrogative sen- tences, other interrogative sentences, and non-question sentences. The different reordering models are developed ori- ented to the different sentence types. Our experiments show that the novel re- ordering models have obtained an im- provement of more than 2.65% in BLEU for a phrase-based spoken language translation sys...