A human evaluation of English-Irish statistical and neural machine translation

Meghan Dowling, Sheila Castilho, Joss Moorkens, Teresa Lynn, Andy Way


Abstract
With official status in both Ireland and the EU, there is a need for high-quality English-Irish (EN-GA) machine translation (MT) systems which are suitable for use in a professional translation environment. While we have seen recent research on improving both statistical MT and neural MT for the EN-GA pair, the results of such systems have always been reported using automatic evaluation metrics. This paper provides the first human evaluation study of EN-GA MT using professional translators and in-domain (public administration) data for a more accurate depiction of the translation quality available via MT.
Anthology ID:
2020.eamt-1.46
Volume:
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
Month:
November
Year:
2020
Address:
Lisboa, Portugal
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation
Note:
Pages:
431–440
Language:
URL:
https://aclanthology.org/2020.eamt-1.46
DOI:
Bibkey:
Cite (ACL):
Meghan Dowling, Sheila Castilho, Joss Moorkens, Teresa Lynn, and Andy Way. 2020. A human evaluation of English-Irish statistical and neural machine translation. In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, pages 431–440, Lisboa, Portugal. European Association for Machine Translation.
Cite (Informal):
A human evaluation of English-Irish statistical and neural machine translation (Dowling et al., EAMT 2020)
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PDF:
https://aclanthology.org/2020.eamt-1.46.pdf