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
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.
Metadata
Item Type: | Article (Published) |
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Refereed: | Yes |
Uncontrolled Keywords: | Gaeilge; English; automatic evaluation metrics |
Subjects: | Computer Science > Computational linguistics Computer Science > Machine translating Humanities > Irish language |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > ADAPT |
Publisher: | Irish Association for Applied Linguistics |
Official URL: | https://doi.org/10.35903/teanga.v26i0.88 |
Copyright Information: | © 2019 The Authors. CC-BY 4.0 |
Funders: | Science Foundation Ireland through the SFI Research Centres Programme, European Regional Development Fund (ERDF) through Grant # 13/RC/2106, Department of Culture, Heritage and the Gaeltacht |
ID Code: | 24030 |
Deposited On: | 17 Dec 2019 13:22 by Meghan Dowling . Last Modified 17 Dec 2019 13:22 |
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