@inproceedings{dowling-etal-2020-human,
title = "A human evaluation of {E}nglish-{I}rish statistical and neural machine translation",
author = "Dowling, Meghan and
Castilho, Sheila and
Moorkens, Joss and
Lynn, Teresa and
Way, Andy",
booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
month = nov,
year = "2020",
address = "Lisboa, Portugal",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2020.eamt-1.46",
pages = "431--440",
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.",
}
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%0 Conference Proceedings
%T A human evaluation of English-Irish statistical and neural machine translation
%A Dowling, Meghan
%A Castilho, Sheila
%A Moorkens, Joss
%A Lynn, Teresa
%A Way, Andy
%S Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
%D 2020
%8 nov
%I European Association for Machine Translation
%C Lisboa, Portugal
%F dowling-etal-2020-human
%X 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.
%U https://aclanthology.org/2020.eamt-1.46
%P 431-440
Markdown (Informal)
[A human evaluation of English-Irish statistical and neural machine translation](https://aclanthology.org/2020.eamt-1.46) (Dowling et al., EAMT 2020)
ACL