The Ubiqus English-Inuktitut System for WMT20

François Hernandez; Vincent Nguyen

The Ubiqus English-Inuktitut System for WMT20

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Abstract

This paper describes Ubiqus’ submission to the WMT20 English-Inuktitut shared news translation task. Our main system, and only submission, is based on a multilingual approach, jointly training a Transformer model on several agglutinative languages. The English-Inuktitut translation task is challenging at every step, from data selection, preparation and tokenization to quality evaluation down the line. Difficulties emerge both because of the peculiarities of the Inuktitut language as well as the low-resource context.

Anthology ID:: 2020.wmt-1.21
Volume:: Proceedings of the Fifth Conference on Machine Translation
Month:: November
Year:: 2020
Address:: Online
Editors:: Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
Venue:: WMT
SIG:: SIGMT
Publisher:: Association for Computational Linguistics
Note:
Pages:: 213–217
Language:
URL:: https://aclanthology.org/2020.wmt-1.21/
DOI:
Bibkey:
Cite (ACL):: François Hernandez and Vincent Nguyen. 2020. The Ubiqus English-Inuktitut System for WMT20. In Proceedings of the Fifth Conference on Machine Translation, pages 213–217, Online. Association for Computational Linguistics.
Cite (Informal):: The Ubiqus English-Inuktitut System for WMT20 (Hernandez & Nguyen, WMT 2020)
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PDF:: https://aclanthology.org/2020.wmt-1.21.pdf

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@inproceedings{hernandez-nguyen-2020-ubiqus,
    title = "The Ubiqus {E}nglish-{I}nuktitut System for {WMT}20",
    author = "Hernandez, Fran{\c{c}}ois  and
      Nguyen, Vincent",
    editor = {Barrault, Lo{\"i}c  and
      Bojar, Ond{\v{r}}ej  and
      Bougares, Fethi  and
      Chatterjee, Rajen  and
      Costa-juss{\`a}, Marta R.  and
      Federmann, Christian  and
      Fishel, Mark  and
      Fraser, Alexander  and
      Graham, Yvette  and
      Guzman, Paco  and
      Haddow, Barry  and
      Huck, Matthias  and
      Yepes, Antonio Jimeno  and
      Koehn, Philipp  and
      Martins, Andr{\'e}  and
      Morishita, Makoto  and
      Monz, Christof  and
      Nagata, Masaaki  and
      Nakazawa, Toshiaki  and
      Negri, Matteo},
    booktitle = "Proceedings of the Fifth Conference on Machine Translation",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.wmt-1.21/",
    pages = "213--217",
    abstract = "This paper describes Ubiqus' submission to the WMT20 English-Inuktitut shared news translation task. Our main system, and only submission, is based on a multilingual approach, jointly training a Transformer model on several agglutinative languages. The English-Inuktitut translation task is challenging at every step, from data selection, preparation and tokenization to quality evaluation down the line. Difficulties emerge both because of the peculiarities of the Inuktitut language as well as the low-resource context."
}

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%0 Conference Proceedings
%T The Ubiqus English-Inuktitut System for WMT20
%A Hernandez, François
%A Nguyen, Vincent
%Y Barrault, Loïc
%Y Bojar, Ondřej
%Y Bougares, Fethi
%Y Chatterjee, Rajen
%Y Costa-jussà, Marta R.
%Y Federmann, Christian
%Y Fishel, Mark
%Y Fraser, Alexander
%Y Graham, Yvette
%Y Guzman, Paco
%Y Haddow, Barry
%Y Huck, Matthias
%Y Yepes, Antonio Jimeno
%Y Koehn, Philipp
%Y Martins, André
%Y Morishita, Makoto
%Y Monz, Christof
%Y Nagata, Masaaki
%Y Nakazawa, Toshiaki
%Y Negri, Matteo
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F hernandez-nguyen-2020-ubiqus
%X This paper describes Ubiqus’ submission to the WMT20 English-Inuktitut shared news translation task. Our main system, and only submission, is based on a multilingual approach, jointly training a Transformer model on several agglutinative languages. The English-Inuktitut translation task is challenging at every step, from data selection, preparation and tokenization to quality evaluation down the line. Difficulties emerge both because of the peculiarities of the Inuktitut language as well as the low-resource context.
%U https://aclanthology.org/2020.wmt-1.21/
%P 213-217

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Markdown (Informal)

[The Ubiqus English-Inuktitut System for WMT20](https://aclanthology.org/2020.wmt-1.21/) (Hernandez & Nguyen, WMT 2020)

The Ubiqus English-Inuktitut System for WMT20 (Hernandez & Nguyen, WMT 2020)

ACL

François Hernandez and Vincent Nguyen. 2020. The Ubiqus English-Inuktitut System for WMT20. In Proceedings of the Fifth Conference on Machine Translation, pages 213–217, Online. Association for Computational Linguistics.