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.
Metadata
Item Type:
Conference or Workshop Item (Paper)
Event Type:
Conference
Refereed:
Yes
Uncontrolled Keywords:
neural machine translation; statistical machine translation; human evaluation; machine translation post-editing; Irish language
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
Science Foundation Ireland through the SFI Research Centres Programme and is co-funded under the European Regional Development Fund through Grant #13/RC/2106.
ID Code:
24418
Deposited On:
30 Apr 2020 11:30 by
Meghan Dowling
. Last Modified 10 Mar 2021 12:06