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English-Basque Statistical and Neural Machine Translation

Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

DOI:10.63317/2qaifpjgg3vf

Abstract

Neural Machine Translation (NMT) has attracted increasing attention in the recent years. However, it tends to require very large training corpora which could prove problematic for languages with low resources. For this reason, Statistical Machine Translation (SMT) continues to be a popular approach for low-resource language pairs. In this work, we address English-Basque translation and compare the performance of three contemporary statistical and neural machine translation systems: OpenNMT, Moses SMT and Google Translate. For evaluation, we employ an open-domain and an IT-domain corpora from the WMT16 resources for machine translation. In addition, we release a small dataset (Berriak) of 500 highly-accurate English-Basque translations of complex sentences useful for a thorough testing of the translation systems.

Details

Paper ID
lrec2018-main-141
Pages
N/A
BibKey
jauregi-unanue-etal-2018-english
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
79-10-95546-00-9
Conference
Eleventh International Conference on Language Resources and Evaluation
Location
Miyazaki, Japan
Date
7 May 2018 12 May 2018

Authors

  • IJ

    Inigo Jauregi Unanue

  • LG

    Lierni Garmendia Arratibel

  • EZ

    Ehsan Zare Borzeshi

  • MP

    Massimo Piccardi

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