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://www.aclweb.org/anthology/2020.eamt-1.46
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.eamt-1.46.pdf