Briva-Iglesias, Vicent and O'Brien, Sharon ORCID: 0000-0003-4864-5986 (2024) Pre-task perceptions of MT influence quality and productivity: the importance of better translator-computer interactions and implications for training. In: 25th Annual Conference of the European Association for Machine Translation, 24-27 June, Sheffield.
Abstract
This paper presents a user study with 11 professional English-Spanish translators in the legal domain. We analysed whether negative or positive translators’ pre-task perceptions of machine translation (MT) being an aid or a threat had any relationship with final translation quality and productivity in a post-editing workflow. Pretask perceptions of MT were collected in a questionnaire before translators conducted
post-editing tasks and were then correlated with translation productivity and translation quality after an Adequacy-Fluency evaluation. Each participant translated 13 texts over two consecutive weeks, accounting for 120,102 words in total. Results show that translators who had higher levels of trust in MT and thought that MT was not a threat to the translation profession reported higher translation quality and productivity. These results have critical implications: improving translator-computer
interactions and fostering MT literacy in translation training may be crucial to reducing negative translators’ pre-task perceptions, resulting in better translation productivity and quality, especially adequacy
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Subjects: | Computer Science > Artificial intelligence Computer Science > Computational linguistics Computer Science > Information technology Humanities > Translating and interpreting |
DCU Faculties and Centres: | UNSPECIFIED |
Published in: | Proceedings of the 25th Annual Conference of the European Association for Machine Translation. . European Association for Machine Translation. |
Publisher: | European Association for Machine Translation |
Official URL: | https://eamt2024.sheffield.ac.uk/ |
Copyright Information: | Authors |
Funders: | SFI CRT in Digitally-Enhanced Reality |
ID Code: | 30108 |
Deposited On: | 02 Jul 2024 08:50 by Vicent Briva Iglesias . Last Modified 02 Jul 2024 08:50 |
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