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Abstract
This paper describes DUT-NLP Lab’s submission to the WMT-21 triangular machine translation shared task. The participants are not allowed to use other data and the translation direction of this task is Russian-to-Chinese. In this task, we use the Transformer as our baseline model, and integrate several techniques to enhance the performance of the baseline, including data filtering, data selection, fine-tuning, and post-editing. Further, to make use of the English resources, such as Russian/English and Chinese/English parallel data, the relationship triangle is constructed by multilingual neural machine translation systems. As a result, our submission achieves a BLEU score of 21.9 in Russian-to-Chinese.- Anthology ID:
- 2021.wmt-1.38
- 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:
- 331–335
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.38/
- DOI:
- Bibkey:
- Cite (ACL):
- Huan Liu, Junpeng Liu, Kaiyu Huang, and Degen Huang. 2021. DUTNLP Machine Translation System for WMT21 Triangular Translation Task. In Proceedings of the Sixth Conference on Machine Translation, pages 331–335, Online. Association for Computational Linguistics.
- Cite (Informal):
- DUTNLP Machine Translation System for WMT21 Triangular Translation Task (Liu et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.38.pdf
Export citation
@inproceedings{liu-etal-2021-dutnlp,
title = "{DUTNLP} Machine Translation System for {WMT}21 Triangular Translation Task",
author = "Liu, Huan and
Liu, Junpeng and
Huang, Kaiyu and
Huang, Degen",
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-1.38/",
pages = "331--335",
abstract = "This paper describes DUT-NLP Lab`s submission to the WMT-21 triangular machine translation shared task. The participants are not allowed to use other data and the translation direction of this task is Russian-to-Chinese. In this task, we use the Transformer as our baseline model, and integrate several techniques to enhance the performance of the baseline, including data filtering, data selection, fine-tuning, and post-editing. Further, to make use of the English resources, such as Russian/English and Chinese/English parallel data, the relationship triangle is constructed by multilingual neural machine translation systems. As a result, our submission achieves a BLEU score of 21.9 in Russian-to-Chinese."
}
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<abstract>This paper describes DUT-NLP Lab‘s submission to the WMT-21 triangular machine translation shared task. The participants are not allowed to use other data and the translation direction of this task is Russian-to-Chinese. In this task, we use the Transformer as our baseline model, and integrate several techniques to enhance the performance of the baseline, including data filtering, data selection, fine-tuning, and post-editing. Further, to make use of the English resources, such as Russian/English and Chinese/English parallel data, the relationship triangle is constructed by multilingual neural machine translation systems. As a result, our submission achieves a BLEU score of 21.9 in Russian-to-Chinese.</abstract>
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%0 Conference Proceedings %T DUTNLP Machine Translation System for WMT21 Triangular Translation Task %A Liu, Huan %A Liu, Junpeng %A Huang, Kaiyu %A Huang, Degen %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 liu-etal-2021-dutnlp %X This paper describes DUT-NLP Lab‘s submission to the WMT-21 triangular machine translation shared task. The participants are not allowed to use other data and the translation direction of this task is Russian-to-Chinese. In this task, we use the Transformer as our baseline model, and integrate several techniques to enhance the performance of the baseline, including data filtering, data selection, fine-tuning, and post-editing. Further, to make use of the English resources, such as Russian/English and Chinese/English parallel data, the relationship triangle is constructed by multilingual neural machine translation systems. As a result, our submission achieves a BLEU score of 21.9 in Russian-to-Chinese. %U https://aclanthology.org/2021.wmt-1.38/ %P 331-335
Markdown (Informal)
[DUTNLP Machine Translation System for WMT21 Triangular Translation Task](https://aclanthology.org/2021.wmt-1.38/) (Liu et al., WMT 2021)
- DUTNLP Machine Translation System for WMT21 Triangular Translation Task (Liu et al., WMT 2021)
ACL
- Huan Liu, Junpeng Liu, Kaiyu Huang, and Degen Huang. 2021. DUTNLP Machine Translation System for WMT21 Triangular Translation Task. In Proceedings of the Sixth Conference on Machine Translation, pages 331–335, Online. Association for Computational Linguistics.