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:
- 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)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2020.eamt-1.46.pdf