CUNI English-Czech and English-Polish Systems in WMT20: Robust Document-Level Training

Martin Popel


Abstract
We describe our two NMT systems submitted to the WMT 2020 shared task in English<->Czech and English<->Polish news translation. One system is sentence level, translating each sentence independently. The second system is document level, translating multiple sentences, trained on multi-sentence sequences up to 3000 characters long.
Anthology ID:
2020.wmt-1.28
Volume:
Proceedings of the Fifth Conference on Machine Translation
Month:
November
Year:
2020
Address:
Online
Editors:
Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
269–273
Language:
URL:
https://aclanthology.org/2020.wmt-1.28
DOI:
Bibkey:
Cite (ACL):
Martin Popel. 2020. CUNI English-Czech and English-Polish Systems in WMT20: Robust Document-Level Training. In Proceedings of the Fifth Conference on Machine Translation, pages 269–273, Online. Association for Computational Linguistics.
Cite (Informal):
CUNI English-Czech and English-Polish Systems in WMT20: Robust Document-Level Training (Popel, WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.28.pdf
Video:
 https://slideslive.com/38939668