Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data

Amittai Axelrod; Anish Kumar; Steve Sloto

doi:10.18653/v1/W19-5433

Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data

Amittai Axelrod, Anish Kumar, Steve Sloto

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Abstract

We introduce a purely monolingual approach to filtering for parallel data from a noisy corpus in a low-resource scenario. Our work is inspired by Junczysdowmunt:2018, but we relax the requirements to allow for cases where no parallel data is available. Our primary contribution is a dual monolingual cross-entropy delta criterion modified from Cynical data selection Axelrod:2017, and is competitive (within 1.8 BLEU) with the best bilingual filtering method when used to train SMT systems. Our approach is featherweight, and runs end-to-end on a standard laptop in three hours.

Anthology ID:: W19-5433
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:: 245–251
Language:
URL:: https://aclanthology.org/W19-5433/
DOI:: 10.18653/v1/W19-5433
Bibkey:
Cite (ACL):: Amittai Axelrod, Anish Kumar, and Steve Sloto. 2019. Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 245–251, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):: Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data (Axelrod et al., WMT 2019)
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PDF:: https://aclanthology.org/W19-5433.pdf
Poster:: W19-5433.Poster.pdf

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@inproceedings{axelrod-etal-2019-dual,
    title = "Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data",
    author = "Axelrod, Amittai  and
      Kumar, Anish  and
      Sloto, Steve",
    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/W19-5433/",
    doi = "10.18653/v1/W19-5433",
    pages = "245--251",
    abstract = "We introduce a purely monolingual approach to filtering for parallel data from a noisy corpus in a low-resource scenario. Our work is inspired by Junczysdowmunt:2018, but we relax the requirements to allow for cases where no parallel data is available. Our primary contribution is a dual monolingual cross-entropy delta criterion modified from Cynical data selection Axelrod:2017, and is competitive (within 1.8 BLEU) with the best bilingual filtering method when used to train SMT systems. Our approach is featherweight, and runs end-to-end on a standard laptop in three hours."
}

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%0 Conference Proceedings
%T Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data
%A Axelrod, Amittai
%A Kumar, Anish
%A Sloto, Steve
%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 axelrod-etal-2019-dual
%X We introduce a purely monolingual approach to filtering for parallel data from a noisy corpus in a low-resource scenario. Our work is inspired by Junczysdowmunt:2018, but we relax the requirements to allow for cases where no parallel data is available. Our primary contribution is a dual monolingual cross-entropy delta criterion modified from Cynical data selection Axelrod:2017, and is competitive (within 1.8 BLEU) with the best bilingual filtering method when used to train SMT systems. Our approach is featherweight, and runs end-to-end on a standard laptop in three hours.
%R 10.18653/v1/W19-5433
%U https://aclanthology.org/W19-5433/
%U https://doi.org/10.18653/v1/W19-5433
%P 245-251

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Markdown (Informal)

[Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data](https://aclanthology.org/W19-5433/) (Axelrod et al., WMT 2019)

Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data (Axelrod et al., WMT 2019)

ACL

Amittai Axelrod, Anish Kumar, and Steve Sloto. 2019. Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 245–251, Florence, Italy. Association for Computational Linguistics.