The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task
Àlex R. Atrio, Gabriel Luthier, Axel Fahy, Giorgos Vernikos, Andrei Popescu-Belis, Ljiljana Dolamic
Abstract
In this paper, we present the systems submitted by our team from the Institute of ICT (HEIG-VD / HES-SO) to the Unsupervised MT and Very Low Resource Supervised MT task. We first study the improvements brought to a baseline system by techniques such as back-translation and initialization from a parent model. We find that both techniques are beneficial and suffice to reach performance that compares with more sophisticated systems from the 2020 task. We then present the application of this system to the 2021 task for low-resource supervised Upper Sorbian (HSB) to German translation, in both directions. Finally, we present a contrastive system for HSB-DE in both directions, and for unsupervised German to Lower Sorbian (DSB) translation, which uses multi-task training with various training schedules to improve over the baseline.- Anthology ID:
- 2021.wmt-1.103
- 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:
- 973–981
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.103
- DOI:
- Bibkey:
- Cite (ACL):
- Àlex R. Atrio, Gabriel Luthier, Axel Fahy, Giorgos Vernikos, Andrei Popescu-Belis, and Ljiljana Dolamic. 2021. The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task. In Proceedings of the Sixth Conference on Machine Translation, pages 973–981, Online. Association for Computational Linguistics.
- Cite (Informal):
- The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task (Atrio et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.103.pdf
- Data
- WMT 2020
Export citation
@inproceedings{atrio-etal-2021-iict,
title = "The {IICT}-Yverdon System for the {WMT} 2021 Unsupervised {MT} and Very Low Resource Supervised {MT} Task",
author = "Atrio, {\`A}lex R. and
Luthier, Gabriel and
Fahy, Axel and
Vernikos, Giorgos and
Popescu-Belis, Andrei and
Dolamic, Ljiljana",
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-1.103",
pages = "973--981",
abstract = "In this paper, we present the systems submitted by our team from the Institute of ICT (HEIG-VD / HES-SO) to the Unsupervised MT and Very Low Resource Supervised MT task. We first study the improvements brought to a baseline system by techniques such as back-translation and initialization from a parent model. We find that both techniques are beneficial and suffice to reach performance that compares with more sophisticated systems from the 2020 task. We then present the application of this system to the 2021 task for low-resource supervised Upper Sorbian (HSB) to German translation, in both directions. Finally, we present a contrastive system for HSB-DE in both directions, and for unsupervised German to Lower Sorbian (DSB) translation, which uses multi-task training with various training schedules to improve over the baseline.",
}
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%0 Conference Proceedings %T The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task %A Atrio, Àlex R. %A Luthier, Gabriel %A Fahy, Axel %A Vernikos, Giorgos %A Popescu-Belis, Andrei %A Dolamic, Ljiljana %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 atrio-etal-2021-iict %X In this paper, we present the systems submitted by our team from the Institute of ICT (HEIG-VD / HES-SO) to the Unsupervised MT and Very Low Resource Supervised MT task. We first study the improvements brought to a baseline system by techniques such as back-translation and initialization from a parent model. We find that both techniques are beneficial and suffice to reach performance that compares with more sophisticated systems from the 2020 task. We then present the application of this system to the 2021 task for low-resource supervised Upper Sorbian (HSB) to German translation, in both directions. Finally, we present a contrastive system for HSB-DE in both directions, and for unsupervised German to Lower Sorbian (DSB) translation, which uses multi-task training with various training schedules to improve over the baseline. %U https://aclanthology.org/2021.wmt-1.103 %P 973-981
Markdown (Informal)
[The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task](https://aclanthology.org/2021.wmt-1.103) (Atrio et al., WMT 2021)
- The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task (Atrio et al., WMT 2021)
ACL
- Àlex R. Atrio, Gabriel Luthier, Axel Fahy, Giorgos Vernikos, Andrei Popescu-Belis, and Ljiljana Dolamic. 2021. The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task. In Proceedings of the Sixth Conference on Machine Translation, pages 973–981, Online. Association for Computational Linguistics.