The NITS-CNLP System for the Unsupervised MT Task at WMT 2020

Salam Michael Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay


Abstract
We describe NITS-CNLP’s submission to WMT 2020 unsupervised machine translation shared task for German language (de) to Upper Sorbian (hsb) in a constrained setting i.e, using only the data provided by the organizers. We train our unsupervised model using monolingual data from both the languages by jointly pre-training the encoder and decoder and fine-tune using backtranslation loss. The final model uses the source side (de) monolingual data and the target side (hsb) synthetic data as a pseudo-parallel data to train a pseudo-supervised system which is tuned using the provided development set(dev set).
Anthology ID:
2020.wmt-1.135
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:
1139–1143
Language:
URL:
https://aclanthology.org/2020.wmt-1.135
DOI:
Bibkey:
Cite (ACL):
Salam Michael Singh, Thoudam Doren Singh, and Sivaji Bandyopadhyay. 2020. The NITS-CNLP System for the Unsupervised MT Task at WMT 2020. In Proceedings of the Fifth Conference on Machine Translation, pages 1139–1143, Online. Association for Computational Linguistics.
Cite (Informal):
The NITS-CNLP System for the Unsupervised MT Task at WMT 2020 (Singh et al., WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.135.pdf
Video:
 https://slideslive.com/38939575