Abstract
This paper describes the participation of team F1toF6 (LTRC, IIIT-Hyderabad) for the WMT 2020 task, similar language translation. We experimented with attention based recurrent neural network architecture (seq2seq) for this task. We explored the use of different linguistic features like POS and Morph along with back translation for Hindi-Marathi and Marathi-Hindi machine translation.- Anthology ID:
- 2020.wmt-1.48
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 414–417
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.48
- DOI:
- Cite (ACL):
- Vandan Mujadia and Dipti Sharma. 2020. NMT based Similar Language Translation for Hindi - Marathi. In Proceedings of the Fifth Conference on Machine Translation, pages 414–417, Online. Association for Computational Linguistics.
- Cite (Informal):
- NMT based Similar Language Translation for Hindi - Marathi (Mujadia & Sharma, WMT 2020)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2020.wmt-1.48.pdf