UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles

Danielle Saunders; Felix Stahlberg; Bill Byrne

doi:10.18653/v1/W19-5421

UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles

Danielle Saunders, Felix Stahlberg, Bill Byrne

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Abstract

The 2019 WMT Biomedical translation task involved translating Medline abstracts. We approached this using transfer learning to obtain a series of strong neural models on distinct domains, and combining them into multi-domain ensembles. We further experimented with an adaptive language-model ensemble weighting scheme. Our submission achieved the best submitted results on both directions of English-Spanish.

Anthology ID:: W19-5421
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:: 169–174
Language:
URL:: https://aclanthology.org/W19-5421/
DOI:: 10.18653/v1/W19-5421
Bibkey:
Cite (ACL):: Danielle Saunders, Felix Stahlberg, and Bill Byrne. 2019. UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 169–174, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):: UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles (Saunders et al., WMT 2019)
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PDF:: https://aclanthology.org/W19-5421.pdf

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@inproceedings{saunders-etal-2019-ucam,
    title = "{UCAM} Biomedical Translation at {WMT}19: Transfer Learning Multi-domain Ensembles",
    author = "Saunders, Danielle  and
      Stahlberg, Felix  and
      Byrne, Bill",
    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/W19-5421/",
    doi = "10.18653/v1/W19-5421",
    pages = "169--174",
    abstract = "The 2019 WMT Biomedical translation task involved translating Medline abstracts. We approached this using transfer learning to obtain a series of strong neural models on distinct domains, and combining them into multi-domain ensembles. We further experimented with an adaptive language-model ensemble weighting scheme. Our submission achieved the best submitted results on both directions of English-Spanish."
}

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%0 Conference Proceedings
%T UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles
%A Saunders, Danielle
%A Stahlberg, Felix
%A Byrne, Bill
%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 saunders-etal-2019-ucam
%X The 2019 WMT Biomedical translation task involved translating Medline abstracts. We approached this using transfer learning to obtain a series of strong neural models on distinct domains, and combining them into multi-domain ensembles. We further experimented with an adaptive language-model ensemble weighting scheme. Our submission achieved the best submitted results on both directions of English-Spanish.
%R 10.18653/v1/W19-5421
%U https://aclanthology.org/W19-5421/
%U https://doi.org/10.18653/v1/W19-5421
%P 169-174

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Markdown (Informal)

[UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles](https://aclanthology.org/W19-5421/) (Saunders et al., WMT 2019)

UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles (Saunders et al., WMT 2019)

ACL

Danielle Saunders, Felix Stahlberg, and Bill Byrne. 2019. UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 169–174, Florence, Italy. Association for Computational Linguistics.