Resende, Natália ORCID: 0000-0002-5248-2457, Cowan, Benjamin ORCID: 0000-0002-8595-8132 and Way, Andy ORCID: 0000-0001-5736-5930 (2020) MT syntactic priming effects on L2 English speakers. In: European Association for Machine Translation (EAMT) 2020, 2-6 Nov 2010, Lisbon, Portugal (Online). ISBN 978-989-33-0589-8
Abstract
In this paper, we tested 20 Brazilian Portuguese speakers at intermediate and ad- vanced English proficiency levels to inves- tigate the influence of Google Translate’s MT system on the mental processing of English as a second language. To this end, we employed a syntactic priming experi- mental paradigm using a pretest-priming design which allowed us to compare par- ticipants’ linguistic behaviour before and after a translation task using Google Trans- late. Results show that, after performing a translation task with Google Translate, participants more frequently described im- ages in English using the syntactic alter- native previously seen in the output of Google Translate, compared to the transla- tion task with no prior influence of the MT output. Results also show that this syntac- tic priming effect is modulated by English proficiency levels.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
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Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Portuguese; Language Learning; Syntactic priming; Syntactic alignment; Translation; Human-Computer interaction |
Subjects: | Computer Science > Artificial intelligence Computer Science > Machine translating Humanities > Language Humanities > Linguistics Humanities > Translating and interpreting Medical Sciences > Psychology |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Institutes and Centres > ADAPT |
Published in: | Proceedings of the 22nd Annual Conference of the European Association for Machine Translation. . European Association for Machine Translation (EAMT). ISBN 978-989-33-0589-8 |
Publisher: | European Association for Machine Translation (EAMT) |
Official URL: | https://www.aclweb.org/anthology/2020.eamt-1.26 |
Copyright Information: | © 2020 The Authors. CC-BY-4.0 |
Funders: | Science Foundation Ireland Research Centres Programme (Grant 13/RC/2106) and is co-funded by the European Regional Development Fund. T, European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant no. 843455. |
ID Code: | 24989 |
Deposited On: | 08 Sep 2020 14:50 by Natalia Resende . Last Modified 10 Mar 2021 12:20 |
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