Contact Relatedness can help improve multilingual NMT: Microsoft STCI-MT @ WMT20

Vikrant Goyal, Anoop Kunchukuttan, Rahul Kejriwal, Siddharth Jain, Amit Bhagwat


Abstract
We describe our submission for the English→Tamil and Tamil→English news translation shared task. In this submission, we focus on exploring if a low-resource language (Tamil) can benefit from a high-resource language (Hindi) with which it shares contact relatedness. We show utilizing contact relatedness via multilingual NMT can significantly improve translation quality for English-Tamil translation.
Anthology ID:
2020.wmt-1.19
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:
202–206
Language:
URL:
https://aclanthology.org/2020.wmt-1.19
DOI:
Bibkey:
Cite (ACL):
Vikrant Goyal, Anoop Kunchukuttan, Rahul Kejriwal, Siddharth Jain, and Amit Bhagwat. 2020. Contact Relatedness can help improve multilingual NMT: Microsoft STCI-MT @ WMT20. In Proceedings of the Fifth Conference on Machine Translation, pages 202–206, Online. Association for Computational Linguistics.
Cite (Informal):
Contact Relatedness can help improve multilingual NMT: Microsoft STCI-MT @ WMT20 (Goyal et al., WMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wmt-1.19.pdf
Video:
 https://slideslive.com/38939654