JU-Saarland Submission to the WMT2019 English–Gujarati Translation Shared Task

Riktim Mondal, Shankha Raj Nayek, Aditya Chowdhury, Santanu Pal, Sudip Kumar Naskar, Josef van Genabith

Abstract
In this paper we describe our joint submission (JU-Saarland) from Jadavpur University and Saarland University in the WMT 2019 news translation shared task for English–Gujarati language pair within the translation task sub-track. Our baseline and primary submissions are built using Recurrent neural network (RNN) based neural machine translation (NMT) system which follows attention mechanism. Given the fact that the two languages belong to different language families and there is not enough parallel data for this language pair, building a high quality NMT system for this language pair is a difficult task. We produced synthetic data through back-translation from available monolingual data. We report the translation quality of our English–Gujarati and Gujarati–English NMT systems trained at word, byte-pair and character encoding levels where RNN at word level is considered as the baseline and used for comparison purpose. Our English–Gujarati system ranked in the second position in the shared task.
Anthology ID:
W19-5332
Volume:
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
Month:
August
Year:
2019
Address:
Florence, Italy
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
308–313
Language:
URL:
https://aclanthology.org/W19-5332
DOI:
10.18653/v1/W19-5332
Bibkey:
Cite (ACL):
Riktim Mondal, Shankha Raj Nayek, Aditya Chowdhury, Santanu Pal, Sudip Kumar Naskar, and Josef van Genabith. 2019. JU-Saarland Submission to the WMT2019 English–Gujarati Translation Shared Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 308–313, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
JU-Saarland Submission to the WMT2019 English–Gujarati Translation Shared Task (Mondal et al., WMT 2019)
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