Abstract
This paper illustrates our approach to the shared task on large-scale multilingual machine translation in the sixth conference on machine translation (WMT-21). In this work, we aim to build a single multilingual translation system with a hypothesis that a universal cross-language representation leads to better multilingual translation performance. We extend the exploration of different back-translation methods from bilingual translation to multilingual translation. Better performance is obtained by the constrained sampling method, which is different from the finding of the bilingual translation. Besides, we also explore the effect of vocabularies and the amount of synthetic data. Surprisingly, the smaller size of vocabularies perform better, and the extensive monolingual English data offers a modest improvement. We submitted to both the small tasks and achieve the second place.- Anthology ID:
- 2021.wmt-1.50
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Editors:
- Loic Barrault, Ondrej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussa, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Tom Kocmi, Andre Martins, Makoto Morishita, Christof Monz
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 418–424
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.50
- DOI:
- Bibkey:
- Cite (ACL):
- Baohao Liao, Shahram Khadivi, and Sanjika Hewavitharana. 2021. Back-translation for Large-Scale Multilingual Machine Translation. In Proceedings of the Sixth Conference on Machine Translation, pages 418–424, Online. Association for Computational Linguistics.
- Cite (Informal):
- Back-translation for Large-Scale Multilingual Machine Translation (Liao et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.50.pdf
- Code
- baohaoliao/multiback
Export citation
@inproceedings{liao-etal-2021-back, title = "Back-translation for Large-Scale Multilingual Machine Translation", author = "Liao, Baohao and Khadivi, Shahram and Hewavitharana, Sanjika", editor = "Barrault, Loic and Bojar, Ondrej and Bougares, Fethi and Chatterjee, Rajen and Costa-jussa, Marta R. and Federmann, Christian and Fishel, Mark and Fraser, Alexander and Freitag, Markus and Graham, Yvette and Grundkiewicz, Roman and Guzman, Paco and Haddow, Barry and Huck, Matthias and Yepes, Antonio Jimeno and Koehn, Philipp and Kocmi, Tom and Martins, Andre and Morishita, Makoto and Monz, Christof", booktitle = "Proceedings of the Sixth Conference on Machine Translation", month = nov, year = "2021", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2021.wmt-1.50", pages = "418--424", abstract = "This paper illustrates our approach to the shared task on large-scale multilingual machine translation in the sixth conference on machine translation (WMT-21). In this work, we aim to build a single multilingual translation system with a hypothesis that a universal cross-language representation leads to better multilingual translation performance. We extend the exploration of different back-translation methods from bilingual translation to multilingual translation. Better performance is obtained by the constrained sampling method, which is different from the finding of the bilingual translation. Besides, we also explore the effect of vocabularies and the amount of synthetic data. Surprisingly, the smaller size of vocabularies perform better, and the extensive monolingual English data offers a modest improvement. We submitted to both the small tasks and achieve the second place.", }
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%0 Conference Proceedings %T Back-translation for Large-Scale Multilingual Machine Translation %A Liao, Baohao %A Khadivi, Shahram %A Hewavitharana, Sanjika %Y Barrault, Loic %Y Bojar, Ondrej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussa, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Freitag, Markus %Y Graham, Yvette %Y Grundkiewicz, Roman %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Kocmi, Tom %Y Martins, Andre %Y Morishita, Makoto %Y Monz, Christof %S Proceedings of the Sixth Conference on Machine Translation %D 2021 %8 November %I Association for Computational Linguistics %C Online %F liao-etal-2021-back %X This paper illustrates our approach to the shared task on large-scale multilingual machine translation in the sixth conference on machine translation (WMT-21). In this work, we aim to build a single multilingual translation system with a hypothesis that a universal cross-language representation leads to better multilingual translation performance. We extend the exploration of different back-translation methods from bilingual translation to multilingual translation. Better performance is obtained by the constrained sampling method, which is different from the finding of the bilingual translation. Besides, we also explore the effect of vocabularies and the amount of synthetic data. Surprisingly, the smaller size of vocabularies perform better, and the extensive monolingual English data offers a modest improvement. We submitted to both the small tasks and achieve the second place. %U https://aclanthology.org/2021.wmt-1.50 %P 418-424
Markdown (Informal)
[Back-translation for Large-Scale Multilingual Machine Translation](https://aclanthology.org/2021.wmt-1.50) (Liao et al., WMT 2021)
- Back-translation for Large-Scale Multilingual Machine Translation (Liao et al., WMT 2021)
ACL
- Baohao Liao, Shahram Khadivi, and Sanjika Hewavitharana. 2021. Back-translation for Large-Scale Multilingual Machine Translation. In Proceedings of the Sixth Conference on Machine Translation, pages 418–424, Online. Association for Computational Linguistics.