The IIIT-H Gujarati-English Machine Translation System for WMT19

Vikrant Goyal, Dipti Misra Sharma


Abstract
This paper describes the Neural Machine Translation system of IIIT-Hyderabad for the Gujarati→English news translation shared task of WMT19. Our system is basedon encoder-decoder framework with attention mechanism. We experimented with Multilingual Neural MT models. Our experiments show that Multilingual Neural Machine Translation leveraging parallel data from related language pairs helps in significant BLEU improvements upto 11.5, for low resource language pairs like Gujarati-English
Anthology ID:
W19-5316
Volume:
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
191–195
Language:
URL:
https://aclanthology.org/W19-5316
DOI:
10.18653/v1/W19-5316
Bibkey:
Cite (ACL):
Vikrant Goyal and Dipti Misra Sharma. 2019. The IIIT-H Gujarati-English Machine Translation System for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 191–195, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
The IIIT-H Gujarati-English Machine Translation System for WMT19 (Goyal & Sharma, WMT 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-5316.pdf