RTM Stacking Results for Machine Translation Performance Prediction

Ergun Bicici

doi:10.18653/v1/W19-5405

RTM Stacking Results for Machine Translation Performance Prediction

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Abstract

We obtain new results using referential translation machines with increased number of learning models in the set of results that are stacked to obtain a better mixture of experts prediction. We combine features extracted from the word-level predictions with the sentence- or document-level features, which significantly improve the results on the training sets but decrease the test set results.

Anthology ID:: W19-5405
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:: 73–77
Language:
URL:: https://aclanthology.org/W19-5405/
DOI:: 10.18653/v1/W19-5405
Bibkey:
Cite (ACL):: Ergun Biçici. 2019. RTM Stacking Results for Machine Translation Performance Prediction. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 73–77, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):: RTM Stacking Results for Machine Translation Performance Prediction (Biçici, WMT 2019)
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PDF:: https://aclanthology.org/W19-5405.pdf

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@inproceedings{bicici-2019-rtm,
    title = "{RTM} Stacking Results for Machine Translation Performance Prediction",
    author = "Bi{\c{c}}ici, Ergun",
    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/W19-5405/",
    doi = "10.18653/v1/W19-5405",
    pages = "73--77",
    abstract = "We obtain new results using referential translation machines with increased number of learning models in the set of results that are stacked to obtain a better mixture of experts prediction. We combine features extracted from the word-level predictions with the sentence- or document-level features, which significantly improve the results on the training sets but decrease the test set results."
}

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%0 Conference Proceedings
%T RTM Stacking Results for Machine Translation Performance Prediction
%A Biçici, Ergun
%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 bicici-2019-rtm
%X We obtain new results using referential translation machines with increased number of learning models in the set of results that are stacked to obtain a better mixture of experts prediction. We combine features extracted from the word-level predictions with the sentence- or document-level features, which significantly improve the results on the training sets but decrease the test set results.
%R 10.18653/v1/W19-5405
%U https://aclanthology.org/W19-5405/
%U https://doi.org/10.18653/v1/W19-5405
%P 73-77

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Markdown (Informal)

[RTM Stacking Results for Machine Translation Performance Prediction](https://aclanthology.org/W19-5405/) (Biçici, WMT 2019)

RTM Stacking Results for Machine Translation Performance Prediction (Biçici, WMT 2019)

ACL

Ergun Biçici. 2019. RTM Stacking Results for Machine Translation Performance Prediction. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 73–77, Florence, Italy. Association for Computational Linguistics.