Syntax- and semantic-based reordering in hierarchical phrase-based statistical machine translation

作者：

Highlights：

• A syntax-based reordering model (RM) for SMT system is proposed.

• Our RM predicts the orientation between syntactic dependants of the source sentence.

• We enrich the proposed RM with semantic features, so it can perform semantic generalization.

• Our RM outperforms the baseline and two competing RMs in terms of BLEU and TER.

摘要

•A syntax-based reordering model (RM) for SMT system is proposed.•Our RM predicts the orientation between syntactic dependants of the source sentence.•We enrich the proposed RM with semantic features, so it can perform semantic generalization.•Our RM outperforms the baseline and two competing RMs in terms of BLEU and TER.

论文关键词：Statistical machine translation,Reordering,Dependency structure,HPB-SMT,Syntax,Semantic

论文评审过程：Received 28 December 2016, Revised 1 May 2017, Accepted 2 May 2017, Available online 5 May 2017, Version of Record 12 May 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.05.001