Faster and lighter phrase-based machine translation baseline

Li Ling Tan, Jon Dehdari, Josef van Genabith

In: The Third Workshop on Asian Translation (WAT2016). Workshop on Asian Translation (WAT-2016) December 12 Osaka Japan Pages 184-193 ISBN 978-4-87974-714-3 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.

Weitere Links

W16-4618.pdf (pdf, 156 KB)

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz