Bicleaner at WMT 2020: Universitat d’Alacant-Prompsit’s submission to the parallel corpus filtering shared task

Miquel Esplà-Gomis, Víctor M. Sánchez-Cartagena, Jaume Zaragoza-Bernabeu, Felipe Sánchez-Martínez


Abstract
This paper describes the joint submission of Universitat d’Alacant and Prompsit Language Engineering to the WMT 2020 shared task on parallel corpus filtering. Our submission, based on the free/open-source tool Bicleaner, enhances it with Extremely Randomised Trees and lexical similarity features that account for the frequency of the words in the parallel sentences to determine if two sentences are parallel. To train this classifier we used the clean corpora provided for the task and synthetic noisy parallel sentences. In addition we re-score the output of Bicleaner using character-level language models and n-gram saturation.
Anthology ID:
2020.wmt-1.107
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:
952–958
Language:
URL:
https://aclanthology.org/2020.wmt-1.107
DOI:
Bibkey:
Cite (ACL):
Miquel Esplà-Gomis, Víctor M. Sánchez-Cartagena, Jaume Zaragoza-Bernabeu, and Felipe Sánchez-Martínez. 2020. Bicleaner at WMT 2020: Universitat d’Alacant-Prompsit’s submission to the parallel corpus filtering shared task. In Proceedings of the Fifth Conference on Machine Translation, pages 952–958, Online. Association for Computational Linguistics.
Cite (Informal):
Bicleaner at WMT 2020: Universitat d’Alacant-Prompsit’s submission to the parallel corpus filtering shared task (Esplà-Gomis et al., WMT 2020)
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https://preview.aclanthology.org/naacl24-info/2020.wmt-1.107.pdf
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