The JHU Machine Translation Systems for WMT 2016
Shuoyang Ding, Kevin Duh, Huda Khayrallah, Philipp Koehn, Matt Post · 2016
This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016).We set up phrase-based, hierarchical phrase-based and syntax-based systems for all 12 language pairs of this year's evaluation campaign.Novel research directions we investigated include: neural probabilistic language models, bilingual neural network language models, morphological segmentation, and the attentionbased neural machine translation model as reranking feature.