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Leveraging backtranslation to improve machine translation for Gaelic language
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In: Dowling, Meghan orcid:0000-0003-1637-4923 , Lynn, Teresa and Way, Andy orcid:0000-0001-5736-5930 (2019) Leveraging backtranslation to improve machine translation for Gaelic language. In: Third Celtic Language Technology Workshop 2019, 19-23 Aug 2019, Dublin, Ireland. (2019)
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Investigating backtranslation for the improvement of English-Irish machine translation
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In: Dowling, Meghan orcid:0000-0003-1637-4923 , Lynn, Teresa and Way, Andy orcid:0000-0001-5736-5930 (2019) Investigating backtranslation for the improvement of English-Irish machine translation. Teanga, 26 . pp. 1-25. ISSN 0332-205X (2019)
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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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Keyword:
automatic evaluation metrics; Computational linguistics; English; Gaeilge; Irish language; Machine translating
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URL: http://doras.dcu.ie/24030/
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