The LMU Munich Unsupervised Machine Translation System for WMT19

Dario Stojanovski; Viktor Hangya; Matthias Huck; Alexander Fraser

doi:10.18653/v1/W19-5344

The LMU Munich Unsupervised Machine Translation System for WMT19

Dario Stojanovski, Viktor Hangya, Matthias Huck, Alexander Fraser

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Abstract

We describe LMU Munich’s machine translation system for German→Czech translation which was used to participate in the WMT19 shared task on unsupervised news translation. We train our model using monolingual data only from both languages. The final model is an unsupervised neural model using established techniques for unsupervised translation such as denoising autoencoding and online back-translation. We bootstrap the model with masked language model pretraining and enhance it with back-translations from an unsupervised phrase-based system which is itself bootstrapped using unsupervised bilingual word embeddings.

Anthology ID:: W19-5344
Volume:: Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
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:: 393–399
Language:
URL:: https://aclanthology.org/W19-5344/
DOI:: 10.18653/v1/W19-5344
Bibkey:
Cite (ACL):: Dario Stojanovski, Viktor Hangya, Matthias Huck, and Alexander Fraser. 2019. The LMU Munich Unsupervised Machine Translation System for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 393–399, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):: The LMU Munich Unsupervised Machine Translation System for WMT19 (Stojanovski et al., WMT 2019)
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PDF:: https://aclanthology.org/W19-5344.pdf

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@inproceedings{stojanovski-etal-2019-lmu,
    title = "The {LMU} {M}unich Unsupervised Machine Translation System for {WMT}19",
    author = "Stojanovski, Dario  and
      Hangya, Viktor  and
      Huck, Matthias  and
      Fraser, Alexander",
    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 2: Shared Task Papers, Day 1)",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-5344/",
    doi = "10.18653/v1/W19-5344",
    pages = "393--399",
    abstract = "We describe LMU Munich{'}s machine translation system for German{\textrightarrow}Czech translation which was used to participate in the WMT19 shared task on unsupervised news translation. We train our model using monolingual data only from both languages. The final model is an unsupervised neural model using established techniques for unsupervised translation such as denoising autoencoding and online back-translation. We bootstrap the model with masked language model pretraining and enhance it with back-translations from an unsupervised phrase-based system which is itself bootstrapped using unsupervised bilingual word embeddings."
}

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%0 Conference Proceedings
%T The LMU Munich Unsupervised Machine Translation System for WMT19
%A Stojanovski, Dario
%A Hangya, Viktor
%A Huck, Matthias
%A Fraser, Alexander
%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 2: Shared Task Papers, Day 1)
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F stojanovski-etal-2019-lmu
%X We describe LMU Munich’s machine translation system for German→Czech translation which was used to participate in the WMT19 shared task on unsupervised news translation. We train our model using monolingual data only from both languages. The final model is an unsupervised neural model using established techniques for unsupervised translation such as denoising autoencoding and online back-translation. We bootstrap the model with masked language model pretraining and enhance it with back-translations from an unsupervised phrase-based system which is itself bootstrapped using unsupervised bilingual word embeddings.
%R 10.18653/v1/W19-5344
%U https://aclanthology.org/W19-5344/
%U https://doi.org/10.18653/v1/W19-5344
%P 393-399

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Markdown (Informal)

[The LMU Munich Unsupervised Machine Translation System for WMT19](https://aclanthology.org/W19-5344/) (Stojanovski et al., WMT 2019)

The LMU Munich Unsupervised Machine Translation System for WMT19 (Stojanovski et al., WMT 2019)

ACL

Dario Stojanovski, Viktor Hangya, Matthias Huck, and Alexander Fraser. 2019. The LMU Munich Unsupervised Machine Translation System for WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 393–399, Florence, Italy. Association for Computational Linguistics.