Abstract
As post-editing of machine translation (PEMT) is becoming one of the most dominant services offered by the language services industry (LSI), efforts are being made to support provision of this service with additional technology. We present text-to-speech (T2S) as a potential attention-raising technology for post-editors. Our study was conducted with university students and included both PEMT and error annotation of a creative text with and without T2S. Focusing on the error annotation data, our analysis finds that participants under-annotated fewer MT errors in the T2S condition compared to the silent condition. At the same time, more over-annotation was recorded. Finally, annotation performance corresponds to participants’ attitudes towards using T2S.- Anthology ID:
- 2022.eamt-1.28
- Volume:
- Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
- Month:
- June
- Year:
- 2022
- Address:
- Ghent, Belgium
- Editors:
- Helena Moniz, Lieve Macken, Andrew Rufener, Loïc Barrault, Marta R. Costa-jussà, Christophe Declercq, Maarit Koponen, Ellie Kemp, Spyridon Pilos, Mikel L. Forcada, Carolina Scarton, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation
- Note:
- Pages:
- 251–259
- Language:
- URL:
- https://aclanthology.org/2022.eamt-1.28
- DOI:
- Cite (ACL):
- Justus Brockmann, Claudia Wiesinger, and Dragoș Ciobanu. 2022. Error Annotation in Post-Editing Machine Translation: Investigating the Impact of Text-to-Speech Technology. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 251–259, Ghent, Belgium. European Association for Machine Translation.
- Cite (Informal):
- Error Annotation in Post-Editing Machine Translation: Investigating the Impact of Text-to-Speech Technology (Brockmann et al., EAMT 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.eamt-1.28.pdf