Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions
Philipp Koehn, Francisco Guzmán, Vishrav Chaudhary, Juan Pino
Correct Metadata for
Abstract
Following the WMT 2018 Shared Task on Parallel Corpus Filtering, we posed the challenge of assigning sentence-level quality scores for very noisy corpora of sentence pairs crawled from the web, with the goal of sub-selecting 2% and 10% of the highest-quality data to be used to train machine translation systems. This year, the task tackled the low resource condition of Nepali-English and Sinhala-English. Eleven participants from companies, national research labs, and universities participated in this task.- Anthology ID:
- W19-5404
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
- 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:
- 54–72
- Language:
- URL:
- https://aclanthology.org/W19-5404/
- DOI:
- 10.18653/v1/W19-5404
- Bibkey:
- Cite (ACL):
- Philipp Koehn, Francisco Guzmán, Vishrav Chaudhary, and Juan Pino. 2019. Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 54–72, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions (Koehn et al., WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5404.pdf
Export citation
@inproceedings{koehn-etal-2019-findings,
title = "Findings of the {WMT} 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions",
author = "Koehn, Philipp and
Guzm{\'a}n, Francisco and
Chaudhary, Vishrav and
Pino, Juan",
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 3: Shared Task Papers, Day 2)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5404/",
doi = "10.18653/v1/W19-5404",
pages = "54--72",
abstract = "Following the WMT 2018 Shared Task on Parallel Corpus Filtering, we posed the challenge of assigning sentence-level quality scores for very noisy corpora of sentence pairs crawled from the web, with the goal of sub-selecting 2{\%} and 10{\%} of the highest-quality data to be used to train machine translation systems. This year, the task tackled the low resource condition of Nepali-English and Sinhala-English. Eleven participants from companies, national research labs, and universities participated in this task."
}
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%0 Conference Proceedings %T Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions %A Koehn, Philipp %A Guzmán, Francisco %A Chaudhary, Vishrav %A Pino, Juan %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 3: Shared Task Papers, Day 2) %D 2019 %8 August %I Association for Computational Linguistics %C Florence, Italy %F koehn-etal-2019-findings %X Following the WMT 2018 Shared Task on Parallel Corpus Filtering, we posed the challenge of assigning sentence-level quality scores for very noisy corpora of sentence pairs crawled from the web, with the goal of sub-selecting 2% and 10% of the highest-quality data to be used to train machine translation systems. This year, the task tackled the low resource condition of Nepali-English and Sinhala-English. Eleven participants from companies, national research labs, and universities participated in this task. %R 10.18653/v1/W19-5404 %U https://aclanthology.org/W19-5404/ %U https://doi.org/10.18653/v1/W19-5404 %P 54-72
Markdown (Informal)
[Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions](https://aclanthology.org/W19-5404/) (Koehn et al., WMT 2019)
- Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions (Koehn et al., WMT 2019)
ACL
- Philipp Koehn, Francisco Guzmán, Vishrav Chaudhary, and Juan Pino. 2019. Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 54–72, Florence, Italy. Association for Computational Linguistics.