IITP-MT System for Gujarati-English News Translation Task at WMT 2019

Sukanta Sen, Kamal Kumar Gupta, Asif Ekbal, Pushpak Bhattacharyya


Abstract
We describe our submission to WMT 2019 News translation shared task for Gujarati-English language pair. We submit constrained systems, i.e, we rely on the data provided for this language pair and do not use any external data. We train Transformer based subword-level neural machine translation (NMT) system using original parallel corpus along with synthetic parallel corpus obtained through back-translation of monolingual data. Our primary systems achieve BLEU scores of 10.4 and 8.1 for Gujarati→English and English→Gujarati, respectively. We observe that incorporating monolingual data through back-translation improves the BLEU score significantly over baseline NMT and SMT systems for this language pair.
Anthology ID:
W19-5346
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:
407–411
Language:
URL:
https://aclanthology.org/W19-5346
DOI:
10.18653/v1/W19-5346
Bibkey:
Cite (ACL):
Sukanta Sen, Kamal Kumar Gupta, Asif Ekbal, and Pushpak Bhattacharyya. 2019. IITP-MT System for Gujarati-English News Translation Task at WMT 2019. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 407–411, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
IITP-MT System for Gujarati-English News Translation Task at WMT 2019 (Sen et al., WMT 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/W19-5346.pdf