Abstract
This paper describes the systems of Fraunhofer FOKUS for the WMT 2019 machine translation robustness task. We have made submissions to the EN-FR, FR-EN, and JA-EN language pairs. The first two were made with a baseline translator, trained on clean data for the WMT 2019 biomedical translation task. These baselines improved over the baselines from the MTNT paper by 2 to 4 BLEU points, but where not trained on the same data. The last one used the same model class and training procedure, with induced typos in the training data to increase the model robustness.- Anthology ID:
- W19-5363
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 537–538
- Language:
- URL:
- https://aclanthology.org/W19-5363
- DOI:
- 10.18653/v1/W19-5363
- Bibkey:
- Cite (ACL):
- Cristian Grozea. 2019. System Description: The Submission of FOKUS to the WMT 19 Robustness Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 537–538, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- System Description: The Submission of FOKUS to the WMT 19 Robustness Task (Grozea, WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5363.pdf
Export citation
@inproceedings{grozea-2019-system,
title = "System Description: The Submission of {FOKUS} to the {WMT} 19 Robustness Task",
author = "Grozea, Cristian",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5363",
doi = "10.18653/v1/W19-5363",
pages = "537--538",
abstract = "This paper describes the systems of Fraunhofer FOKUS for the WMT 2019 machine translation robustness task. We have made submissions to the EN-FR, FR-EN, and JA-EN language pairs. The first two were made with a baseline translator, trained on clean data for the WMT 2019 biomedical translation task. These baselines improved over the baselines from the MTNT paper by 2 to 4 BLEU points, but where not trained on the same data. The last one used the same model class and training procedure, with induced typos in the training data to increase the model robustness.",
}
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<abstract>This paper describes the systems of Fraunhofer FOKUS for the WMT 2019 machine translation robustness task. We have made submissions to the EN-FR, FR-EN, and JA-EN language pairs. The first two were made with a baseline translator, trained on clean data for the WMT 2019 biomedical translation task. These baselines improved over the baselines from the MTNT paper by 2 to 4 BLEU points, but where not trained on the same data. The last one used the same model class and training procedure, with induced typos in the training data to increase the model robustness.</abstract>
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%0 Conference Proceedings %T System Description: The Submission of FOKUS to the WMT 19 Robustness Task %A Grozea, Cristian %Y Bojar, Ondřej %Y Chatterjee, Rajen %Y Federmann, Christian %Y Fishel, Mark %Y Graham, Yvette %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Monz, Christof %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Post, Matt %Y Turchi, Marco %Y Verspoor, Karin %S Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) %D 2019 %8 August %I Association for Computational Linguistics %C Florence, Italy %F grozea-2019-system %X This paper describes the systems of Fraunhofer FOKUS for the WMT 2019 machine translation robustness task. We have made submissions to the EN-FR, FR-EN, and JA-EN language pairs. The first two were made with a baseline translator, trained on clean data for the WMT 2019 biomedical translation task. These baselines improved over the baselines from the MTNT paper by 2 to 4 BLEU points, but where not trained on the same data. The last one used the same model class and training procedure, with induced typos in the training data to increase the model robustness. %R 10.18653/v1/W19-5363 %U https://aclanthology.org/W19-5363 %U https://doi.org/10.18653/v1/W19-5363 %P 537-538
Markdown (Informal)
[System Description: The Submission of FOKUS to the WMT 19 Robustness Task](https://aclanthology.org/W19-5363) (Grozea, WMT 2019)
- System Description: The Submission of FOKUS to the WMT 19 Robustness Task (Grozea, WMT 2019)
ACL
- Cristian Grozea. 2019. System Description: The Submission of FOKUS to the WMT 19 Robustness Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 537–538, Florence, Italy. Association for Computational Linguistics.