DFKI-LT - Faster and lighter phrase-based machine translation baseline

Li Ling Tan, Jonathan Dehdari, Josef van Genabith
Faster and lighter phrase-based machine translation baseline
3 The Third Workshop on Asian Translation (WAT2016), Pages 184-193, Osaka, Japan, Association for Computational Linguistics, 12/2016
 
This paper describes the SENSE machine translation system participation in the Third Workshop for Asian Translation (WAT2016). We share our best practices to build a fast and light phrase-based machine translation (PBMT) models that have comparable results to the baseline systems provided by the organizers. As Neural Machine Translation (NMT) overtakes PBMT as the state-of-the-art, deep learning and new MT practitioners might not be familiar with the PBMT paradigm and we hope that this paper will help them build a PBMT baseline system quickly and easily.
 
Files: BibTeX, W16-4618.pdf, W16-4618.pdf