Way, Andy ORCID: 0000-0001-5736-5930 (2018) Quality expectations of machine translation. In: Moorkens, Joss ORCID: 0000-0003-4864-5986, Castilho, Sheila ORCID: 0000-0002-8416-6555, Gaspari, Federico ORCID: 0000-0003-3808-8418 and Doherty, Stephen ORCID: 0000-0003-0887-1049, (eds.) Translation Quality Assessment: From Principles to Practice. Machine Translation: Technologies and Applications Series Volume, 1 . Springer, Berlin/Heidelberg, pp. 159-178. ISBN 978-3-319-91240-0
Abstract
Machine Translation (MT) is being deployed for a range of use-cases by millions of people on a daily basis. There should, therefore, be no doubt as to the utility of MT. However, not everyone is convinced that MT can be useful, especially as a productivity enhancer for human translators. In this chapter, I address this issue, describing how MT is currently deployed, how its output is evaluated and how this could be enhanced, especially as MT quality itself improves. Central to these issues is the acceptance that there is no longer a single ‘gold standard’ measure of quality, such that the situation in which MT is deployed needs to be borne in mind, especially with respect to the expected ‘shelf-life’ of the translation itself.
Metadata
Item Type: | Book Section |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | Translation quality assessment ;Translation metrics; Neural machine translation;Translator productivity;Translation users |
Subjects: | Computer Science > Machine translating |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > ADAPT |
Publisher: | Springer |
Official URL: | http://dx.doi.org/10.1007/978-3-319-91241-7_8 |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Science Foundation Ireland (SFI) Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund. |
ID Code: | 24600 |
Deposited On: | 06 Jul 2020 11:09 by Vidatum Academic . Last Modified 24 Jul 2020 11:03 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
757kB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record