Abstract
This paper describes the University of Helsinki Language Technology group’s participation in the WMT 2019 parallel corpus filtering task. Our scores were produced using a two-step strategy. First, we individually applied a series of filters to remove the ‘bad’ quality sentences. Then, we produced scores for each sentence by weighting these features with a classification model. This methodology allowed us to build a simple and reliable system that is easily adaptable to other language pairs.- Anthology ID:
- W19-5441
- 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:
- 294–300
- Language:
- URL:
- https://aclanthology.org/W19-5441
- DOI:
- 10.18653/v1/W19-5441
- Bibkey:
- Cite (ACL):
- Raúl Vázquez, Umut Sulubacak, and Jörg Tiedemann. 2019. The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 294–300, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task (Vázquez et al., WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5441.pdf
Export citation
@inproceedings{vazquez-etal-2019-university,
title = "The {U}niversity of {H}elsinki Submission to the {WMT}19 Parallel Corpus Filtering Task",
author = {V{\'a}zquez, Ra{\'u}l and
Sulubacak, Umut and
Tiedemann, J{\"o}rg},
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/W19-5441",
doi = "10.18653/v1/W19-5441",
pages = "294--300",
abstract = "This paper describes the University of Helsinki Language Technology group{'}s participation in the WMT 2019 parallel corpus filtering task. Our scores were produced using a two-step strategy. First, we individually applied a series of filters to remove the {`}bad{'} quality sentences. Then, we produced scores for each sentence by weighting these features with a classification model. This methodology allowed us to build a simple and reliable system that is easily adaptable to other language pairs.",
}
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%0 Conference Proceedings %T The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task %A Vázquez, Raúl %A Sulubacak, Umut %A Tiedemann, Jörg %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 vazquez-etal-2019-university %X This paper describes the University of Helsinki Language Technology group’s participation in the WMT 2019 parallel corpus filtering task. Our scores were produced using a two-step strategy. First, we individually applied a series of filters to remove the ‘bad’ quality sentences. Then, we produced scores for each sentence by weighting these features with a classification model. This methodology allowed us to build a simple and reliable system that is easily adaptable to other language pairs. %R 10.18653/v1/W19-5441 %U https://aclanthology.org/W19-5441 %U https://doi.org/10.18653/v1/W19-5441 %P 294-300
Markdown (Informal)
[The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task](https://aclanthology.org/W19-5441) (Vázquez et al., WMT 2019)
- The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task (Vázquez et al., WMT 2019)
ACL
- Raúl Vázquez, Umut Sulubacak, and Jörg Tiedemann. 2019. The University of Helsinki Submission to the WMT19 Parallel Corpus Filtering Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 294–300, Florence, Italy. Association for Computational Linguistics.