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
Venues:
EMNLP | 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)
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PDF:
https://preview.aclanthology.org/update-css-js/2020.wmt-1.19.pdf
Video:
 https://slideslive.com/38939654