2020

Tigrinya Neural Machine Translation with Transfer Learning for Humanitarian Response

Öktem, Alp, Plitt, Mirko, Tang, Grace

Understand

We report our experiments in building a domain-specific Tigrinya-to-English neural machine translation system.

  • We use transfer learning from other Ge'ez script languages and report an improvement of 1.3 BLEU points over a classic neural baseline.
  • We publish our development pipeline as an open-source library and also provide a demonstration application.

Built on

  • Bleu: a method for automatic evaluation of machine translation

    Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002

    Earlier work this paper cites.

  • Moses: Open source toolkit for statistical machine translation

    Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondřej Bojar, Alexandra Constantin, and Evan Herbst · 2007

    Earlier work this paper cites.

  • Meteor: An automatic metric for mt evaluation with high levels of correlation with human judgments

    Alon Lavie and Abhaya Agarwal · 2007

    Earlier work this paper cites.

  • Parallel data, tools and interfaces in opus

    Jörg Tiedemann · 2012

    Earlier work this paper cites.

  • Recurrent continuous translation models

    Nal Kalchbrenner and Phil Blunsom · 2013

    Earlier work this paper cites.

  • Adam: A method for stochastic optimization

    Original

    Diederik P. Kingma and Jimmy Ba · 2014

    Earlier work this paper cites.

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Then

  • Transfer learning for low-resource neural machine translation

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