Abstract
In this paper, we describe IIT Delhi’s submissions to the WMT 2020 task on Similar Language Translation for four language directions: Hindi <-> Marathi and Spanish <-> Portuguese. We try out three different model settings for the translation task and select our primary and contrastive submissions on the basis of performance of these three models. For our best submissions, we fine-tune the mBART model on the parallel data provided for the task. The pre-training is done using self-supervised objectives on a large amount of monolingual data for many languages. Overall, our models are ranked in the top four of all systems for the submitted language pairs, with first rank in Spanish -> Portuguese.- Anthology ID:
- 2020.wmt-1.46
- 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:
- 402–408
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.46
- DOI:
- Bibkey:
- Cite (ACL):
- Lovish Madaan, Soumya Sharma, and Parag Singla. 2020. Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 402–408, Online. Association for Computational Linguistics.
- Cite (Informal):
- Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task (Madaan et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.46.pdf
- Video:
- https://slideslive.com/38939620
Export citation
@inproceedings{madaan-etal-2020-transfer, title = "Transfer Learning for Related Languages: Submissions to the {WMT}20 Similar Language Translation Task", author = "Madaan, Lovish and Sharma, Soumya and Singla, Parag", editor = {Barrault, Lo{\"\i}c and Bojar, Ond{\v{r}}ej and Bougares, Fethi and Chatterjee, Rajen and Costa-juss{\`a}, Marta R. and Federmann, Christian and Fishel, Mark and Fraser, Alexander and Graham, Yvette and Guzman, Paco and Haddow, Barry and Huck, Matthias and Yepes, Antonio Jimeno and Koehn, Philipp and Martins, Andr{\'e} and Morishita, Makoto and Monz, Christof and Nagata, Masaaki and Nakazawa, Toshiaki and Negri, Matteo}, booktitle = "Proceedings of the Fifth Conference on Machine Translation", month = nov, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2020.wmt-1.46", pages = "402--408", abstract = "In this paper, we describe IIT Delhi{'}s submissions to the WMT 2020 task on Similar Language Translation for four language directions: Hindi {\textless}-{\textgreater} Marathi and Spanish {\textless}-{\textgreater} Portuguese. We try out three different model settings for the translation task and select our primary and contrastive submissions on the basis of performance of these three models. For our best submissions, we fine-tune the mBART model on the parallel data provided for the task. The pre-training is done using self-supervised objectives on a large amount of monolingual data for many languages. Overall, our models are ranked in the top four of all systems for the submitted language pairs, with first rank in Spanish -{\textgreater} Portuguese.", }
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%0 Conference Proceedings %T Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task %A Madaan, Lovish %A Sharma, Soumya %A Singla, Parag %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Graham, Yvette %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %S Proceedings of the Fifth Conference on Machine Translation %D 2020 %8 November %I Association for Computational Linguistics %C Online %F madaan-etal-2020-transfer %X In this paper, we describe IIT Delhi’s submissions to the WMT 2020 task on Similar Language Translation for four language directions: Hindi \textless-\textgreater Marathi and Spanish \textless-\textgreater Portuguese. We try out three different model settings for the translation task and select our primary and contrastive submissions on the basis of performance of these three models. For our best submissions, we fine-tune the mBART model on the parallel data provided for the task. The pre-training is done using self-supervised objectives on a large amount of monolingual data for many languages. Overall, our models are ranked in the top four of all systems for the submitted language pairs, with first rank in Spanish -\textgreater Portuguese. %U https://aclanthology.org/2020.wmt-1.46 %P 402-408
Markdown (Informal)
[Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task](https://aclanthology.org/2020.wmt-1.46) (Madaan et al., WMT 2020)
- Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task (Madaan et al., WMT 2020)
ACL
- Lovish Madaan, Soumya Sharma, and Parag Singla. 2020. Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 402–408, Online. Association for Computational Linguistics.