Abstract
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.- Anthology ID:
- W16-4618
- Volume:
- Proceedings of the 3rd Workshop on Asian Translation (WAT2016)
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editors:
- Toshiaki Nakazawa, Hideya Mino, Chenchen Ding, Isao Goto, Graham Neubig, Sadao Kurohashi, Ir. Hammam Riza, Pushpak Bhattacharyya
- Venue:
- WAT
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 184–193
- Language:
- URL:
- https://aclanthology.org/W16-4618
- DOI:
- Cite (ACL):
- Liling Tan. 2016. Faster and Lighter Phrase-based Machine Translation Baseline. In Proceedings of the 3rd Workshop on Asian Translation (WAT2016), pages 184–193, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Faster and Lighter Phrase-based Machine Translation Baseline (Tan, WAT 2016)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/W16-4618.pdf