Abstract
This paper describes the Neural Machine Translation systems of IIIT-Hyderabad (LTRC-MT) for WAT 2019 Hindi-English shared task. We experimented with both Recurrent Neural Networks & Transformer architectures. We also show the results of our experiments of training NMT models using additional data via backtranslation.- Anthology ID:
- D19-5216
- Volume:
- Proceedings of the 6th Workshop on Asian Translation
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Toshiaki Nakazawa, Chenchen Ding, Raj Dabre, Anoop Kunchukuttan, Nobushige Doi, Yusuke Oda, Ondřej Bojar, Shantipriya Parida, Isao Goto, Hidaya Mino
- Venue:
- WAT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 137–140
- Language:
- URL:
- https://aclanthology.org/D19-5216
- DOI:
- 10.18653/v1/D19-5216
- Cite (ACL):
- Vikrant Goyal and Dipti Misra Sharma. 2019. LTRC-MT Simple & Effective Hindi-English Neural Machine Translation Systems at WAT 2019. In Proceedings of the 6th Workshop on Asian Translation, pages 137–140, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- LTRC-MT Simple & Effective Hindi-English Neural Machine Translation Systems at WAT 2019 (Goyal & Sharma, WAT 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/D19-5216.pdf