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Abstract
This paper describes our submission for the English-Tamil news translation task of WMT-2020. The various techniques and Neural Machine Translation (NMT) models used by our team are presented and discussed, including back-translation, fine-tuning and word dropout. Additionally, our experiments show that using a linguistically motivated subword segmentation technique (Ataman et al., 2017) does not consistently outperform the more widely used, non-linguistically motivated SentencePiece algorithm (Kudo and Richardson, 2018), despite the agglutinative nature of Tamil morphology.- Anthology ID:
- 2020.wmt-1.9
- 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:
- 126–133
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.9/
- DOI:
- 10.18653/v1/2020.wmt-1.9
- Bibkey:
- Cite (ACL):
- Prajit Dhar, Arianna Bisazza, and Gertjan van Noord. 2020. Linguistically Motivated Subwords for English-Tamil Translation: University of Groningen’s Submission to WMT-2020. In Proceedings of the Fifth Conference on Machine Translation, pages 126–133, Online. Association for Computational Linguistics.
- Cite (Informal):
- Linguistically Motivated Subwords for English-Tamil Translation: University of Groningen’s Submission to WMT-2020 (Dhar et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.9.pdf
- Video:
- https://slideslive.com/38939635
Export citation
@inproceedings{dhar-etal-2020-linguistically,
title = "Linguistically Motivated Subwords for {E}nglish-{T}amil Translation: {U}niversity of {G}roningen{'}s Submission to {WMT}-2020",
author = "Dhar, Prajit and
Bisazza, Arianna and
van Noord, Gertjan",
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-1.9/",
doi = "10.18653/v1/2020.wmt-1.9",
pages = "126--133",
abstract = "This paper describes our submission for the English-Tamil news translation task of WMT-2020. The various techniques and Neural Machine Translation (NMT) models used by our team are presented and discussed, including back-translation, fine-tuning and word dropout. Additionally, our experiments show that using a linguistically motivated subword segmentation technique (Ataman et al., 2017) does not consistently outperform the more widely used, non-linguistically motivated SentencePiece algorithm (Kudo and Richardson, 2018), despite the agglutinative nature of Tamil morphology."
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%0 Conference Proceedings %T Linguistically Motivated Subwords for English-Tamil Translation: University of Groningen’s Submission to WMT-2020 %A Dhar, Prajit %A Bisazza, Arianna %A van Noord, Gertjan %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 dhar-etal-2020-linguistically %X This paper describes our submission for the English-Tamil news translation task of WMT-2020. The various techniques and Neural Machine Translation (NMT) models used by our team are presented and discussed, including back-translation, fine-tuning and word dropout. Additionally, our experiments show that using a linguistically motivated subword segmentation technique (Ataman et al., 2017) does not consistently outperform the more widely used, non-linguistically motivated SentencePiece algorithm (Kudo and Richardson, 2018), despite the agglutinative nature of Tamil morphology. %R 10.18653/v1/2020.wmt-1.9 %U https://aclanthology.org/2020.wmt-1.9/ %U https://doi.org/10.18653/v1/2020.wmt-1.9 %P 126-133
Markdown (Informal)
[Linguistically Motivated Subwords for English-Tamil Translation: University of Groningen’s Submission to WMT-2020](https://aclanthology.org/2020.wmt-1.9/) (Dhar et al., WMT 2020)
- Linguistically Motivated Subwords for English-Tamil Translation: University of Groningen’s Submission to WMT-2020 (Dhar et al., WMT 2020)
ACL
- Prajit Dhar, Arianna Bisazza, and Gertjan van Noord. 2020. Linguistically Motivated Subwords for English-Tamil Translation: University of Groningen’s Submission to WMT-2020. In Proceedings of the Fifth Conference on Machine Translation, pages 126–133, Online. Association for Computational Linguistics.