@inproceedings{zaragoza-bernabeu-etal-2022-bicleaner,
title = "Bicleaner {AI}: Bicleaner Goes Neural",
author = "Zaragoza-Bernabeu, Jaume and
Ram{\'\i}rez-S{\'a}nchez, Gema and
Ba{\~n}{\'o}n, Marta and
Ortiz Rojas, Sergio",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.87",
pages = "824--831",
abstract = "This paper describes the experiments carried out during the development of the latest version of Bicleaner, named Bicleaner AI, a tool that aims at detecting noisy sentences in parallel corpora. The tool, which now implements a new neural classifier, uses state-of-the-art techniques based on pre-trained transformer-based language models fine-tuned on a binary classification task. After that, parallel corpus filtering is performed, discarding the sentences that have lower probability of being mutual translations. Our experiments, based on the training of neural machine translation (NMT) with corpora filtered using Bicleaner AI for two different scenarios, show significant improvements in translation quality compared to the previous version of the tool which implemented a classifier based on Extremely Randomized Trees.",
}
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%0 Conference Proceedings
%T Bicleaner AI: Bicleaner Goes Neural
%A Zaragoza-Bernabeu, Jaume
%A Ramírez-Sánchez, Gema
%A Bañón, Marta
%A Ortiz Rojas, Sergio
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Thirteenth Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F zaragoza-bernabeu-etal-2022-bicleaner
%X This paper describes the experiments carried out during the development of the latest version of Bicleaner, named Bicleaner AI, a tool that aims at detecting noisy sentences in parallel corpora. The tool, which now implements a new neural classifier, uses state-of-the-art techniques based on pre-trained transformer-based language models fine-tuned on a binary classification task. After that, parallel corpus filtering is performed, discarding the sentences that have lower probability of being mutual translations. Our experiments, based on the training of neural machine translation (NMT) with corpora filtered using Bicleaner AI for two different scenarios, show significant improvements in translation quality compared to the previous version of the tool which implemented a classifier based on Extremely Randomized Trees.
%U https://aclanthology.org/2022.lrec-1.87
%P 824-831
Markdown (Informal)
[Bicleaner AI: Bicleaner Goes Neural](https://aclanthology.org/2022.lrec-1.87) (Zaragoza-Bernabeu et al., LREC 2022)
ACL
- Jaume Zaragoza-Bernabeu, Gema Ramírez-Sánchez, Marta Bañón, and Sergio Ortiz Rojas. 2022. Bicleaner AI: Bicleaner Goes Neural. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 824–831, Marseille, France. European Language Resources Association.