Abstract
Schaeffer et al. (2019) studied whether translation student’s error recognition processes dif- fered from those in professional translators. The stimuli consisted of complete texts, which contained errors of five kinds, following Mertin’s (2006) error typology. Translation students and professionals saw translations which contained errors produced by human translators and which had to be revised. Vardaro et al (2019) followed the same logic, but first determined the frequency of error types produced by the EU commission’s NMT system and then pre- sented single sentences containing errors based on the MQM typology. Participants in Vardaro et al (2019) were professional translators employed by the EU. For the current pur- pose, we present the results from a comparison between those 30 professionals in Vardaro et al (2019) and a group of 30 translation students. We presented the same materials as in Vardaro et al (2019) and tracked participants’ eye movements and keystrokes. Results show that translation competence interacts with how errors are recognized and corrected during post-editing. We discuss the results of this study in relation to current models of the transla- tion process by contrasting the predictions these make with the evidence from our study- Anthology ID:
- 2022.amta-wetpr.5
- Volume:
- Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Workshop 1: Empirical Translation Process Research)
- Month:
- September
- Year:
- 2022
- Address:
- Editors:
- Michael Carl, Masaru Yamada, Longui Zou
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 41–48
- Language:
- URL:
- https://aclanthology.org/2022.amta-wetpr.5
- DOI:
- Cite (ACL):
- Moritz J Schaeffer. 2022. The impact of translation competence on error recognition of neural MT. In Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Workshop 1: Empirical Translation Process Research), pages 41–48, None. Association for Machine Translation in the Americas.
- Cite (Informal):
- The impact of translation competence on error recognition of neural MT (Schaeffer, AMTA 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.amta-wetpr.5.pdf