A Discriminative Model for Semantics-to-String Translation

Proc. of S2MT |

论文与出版物

We present a feature-rich discriminative model for machine translation which uses an abstract semantic representation on the source side. We include our model as an additional feature in a phrase-based decoder and we show modest gains in BLEU score in an n-best re-ranking experiment.