The ADAPT System Description for the WMT20 News Translation Task

Venkatesh Parthasarathy, Akshai Ramesh, Rejwanul Haque, Andy Way


Abstract
This paper describes the ADAPT Centre’s submissions to the WMT20 News translation shared task for English-to-Tamil and Tamil-to-English. We present our machine translation (MT) systems that were built using the state-of-the-art neural MT (NMT) model, Transformer. We applied various strategies in order to improve our baseline MT systems, e.g. onolin- gual sentence selection for creating synthetic training data, mining monolingual sentences for adapting our MT systems to the task, hyperparameters search for Transformer in lowresource scenarios. Our experiments show that adding the aforementioned techniques to the baseline yields an excellent performance in the English-to-Tamil and Tamil-to-English translation tasks.
Anthology ID:
2020.wmt-1.27
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:
262–268
Language:
URL:
https://aclanthology.org/2020.wmt-1.27
DOI:
Bibkey:
Cite (ACL):
Venkatesh Parthasarathy, Akshai Ramesh, Rejwanul Haque, and Andy Way. 2020. The ADAPT System Description for the WMT20 News Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 262–268, Online. Association for Computational Linguistics.
Cite (Informal):
The ADAPT System Description for the WMT20 News Translation Task (Parthasarathy et al., WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.27.pdf
Video:
 https://slideslive.com/38939616
Data
WikiMatrix