Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment
Philipp Koehn, Vishrav Chaudhary, Ahmed El-Kishky, Naman Goyal, Peng-Jen Chen, Francisco Guzmán
Correct Metadata for
Abstract
Following two preceding WMT Shared Task on Parallel Corpus Filtering (Koehn et al., 2018, 2019), we posed again 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 the highest-quality data to be used to train ma-chine translation systems. This year, the task tackled the low resource condition of Pashto–English and Khmer–English and also included the challenge of sentence alignment from document pairs.- Anthology ID:
- 2020.wmt-1.78
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 726–742
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.78/
- DOI:
- Bibkey:
- Cite (ACL):
- Philipp Koehn, Vishrav Chaudhary, Ahmed El-Kishky, Naman Goyal, Peng-Jen Chen, and Francisco Guzmán. 2020. Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment. In Proceedings of the Fifth Conference on Machine Translation, pages 726–742, Online. Association for Computational Linguistics.
- Cite (Informal):
- Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment (Koehn et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.78.pdf
- Video:
- https://slideslive.com/38939678
- Data
- CCAligned, ParaCrawl
Export citation
@inproceedings{koehn-etal-2020-findings,
title = "Findings of the {WMT} 2020 Shared Task on Parallel Corpus Filtering and Alignment",
author = "Koehn, Philipp and
Chaudhary, Vishrav and
El-Kishky, Ahmed and
Goyal, Naman and
Chen, Peng-Jen and
Guzm{\'a}n, Francisco",
editor = {Barrault, Lo{\"i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Graham, Yvette and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo},
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.78/",
pages = "726--742",
abstract = "Following two preceding WMT Shared Task on Parallel Corpus Filtering (Koehn et al., 2018, 2019), we posed again 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 the highest-quality data to be used to train ma-chine translation systems. This year, the task tackled the low resource condition of Pashto{--}English and Khmer{--}English and also included the challenge of sentence alignment from document pairs."
}
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%0 Conference Proceedings %T Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment %A Koehn, Philipp %A Chaudhary, Vishrav %A El-Kishky, Ahmed %A Goyal, Naman %A Chen, Peng-Jen %A Guzmán, Francisco %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Graham, Yvette %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %S Proceedings of the Fifth Conference on Machine Translation %D 2020 %8 November %I Association for Computational Linguistics %C Online %F koehn-etal-2020-findings %X Following two preceding WMT Shared Task on Parallel Corpus Filtering (Koehn et al., 2018, 2019), we posed again 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 the highest-quality data to be used to train ma-chine translation systems. This year, the task tackled the low resource condition of Pashto–English and Khmer–English and also included the challenge of sentence alignment from document pairs. %U https://aclanthology.org/2020.wmt-1.78/ %P 726-742
Markdown (Informal)
[Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment](https://aclanthology.org/2020.wmt-1.78/) (Koehn et al., WMT 2020)
- Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment (Koehn et al., WMT 2020)
ACL
- Philipp Koehn, Vishrav Chaudhary, Ahmed El-Kishky, Naman Goyal, Peng-Jen Chen, and Francisco Guzmán. 2020. Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment. In Proceedings of the Fifth Conference on Machine Translation, pages 726–742, Online. Association for Computational Linguistics.