Investigating backtranslation for the improvement of English-Irish machine translation

Authors

  • Meghan Dowling ADAPT Centre, Dublin City University
  • Teresa Lynn ADAPT Centre, Dublin City University
  • Andy Way ADAPT Centre, Dublin City University

DOI:

https://doi.org/10.35903/teanga.v26i0.88

Keywords:

Machine translation, Backtranslation, Irish language, Automatic Evaluation Metrics

Abstract

In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.

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Published

2019-11-29

How to Cite

Dowling, M., Lynn, T., & Way, A. (2019). Investigating backtranslation for the improvement of English-Irish machine translation. TEANGA, the Journal of the Irish Association for Applied Linguistics, 26, 1–25. https://doi.org/10.35903/teanga.v26i0.88

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Section

Articles