Research on Non-contiguous Phrase-based Model for Statistical Machine Translation

The phrase-based statistical machine translation model is still the most popular model nowadays.However,non-contiguous phrases are not taken into account in this model.A statistical machine translation model based on non-contiguous phrases is proposed in this paper.The units of translation are extended from contiguous phrases to phrases with intervals in order to take advantage of the context dependence.With the less numbers of phrases,the efficiency of the decoder in our model is also improved.Experiments show that with a better efficiency the translation results of our non-contiguous phrase-based model and hierarchical model are comparable.