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Translation dictation vs. post-editing with cloud-based voice recognition: a pilot experiment

Zapata, Julián, Castilho, Sheila ORCID: 0000-0002-8416-6555 and Moorkens, Joss ORCID: 0000-0003-0766-0071 (2017) Translation dictation vs. post-editing with cloud-based voice recognition: a pilot experiment. In: MT Summit XVI, 18-22 Sept 2017, At Nagoya, Japan.

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Abstract

In this paper, we report on a pilot mixed-methods experiment investigating the effects on productivity and on the translator experience of integrating machine translation (MT) postediting (PE) with voice recognition (VR) and translation dictation (TD). The experiment was performed with a sample of native Spanish participants. In the quantitative phase of the experiment, they performed four tasks under four different conditions, namely (1) conventional TD; (2) PE in dictation mode; (3) TD with VR; and (4) PE with VR (PEVR). In the follow-on qualitative phase, the participants filled out an online survey, providing details of their perceptions of the task and of PEVR in general. Our results suggest that PEVR may be a usable way to add MT to a translation workflow, with some caveats. When asked about their experience with the tasks, our participants preferred translation without the ‘constraint’ of MT, though the quantitative results show that PE tasks were generally more efficient. This paper provides a brief overview of past work exploring VR for from-scratch translation and PE purposes, describes our pilot experiment in detail, presents an overview and analysis of the data collected, and outlines avenues for future work.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
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
Published in: Yamada, Masaru and Seligman, Mark, (eds.) MT Summit XVI Proceedings: Users and Translators Track. 2. MT Summit.
Publisher:MT Summit
Official URL:http://aamt.info/app-def/S-102/mtsummit/2017/wp-content/uploads/sites/2/2017/09/MTSummitXVI_UserTrack.pdf
Copyright Information:© 2017 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:SFI Research Centres Programme (Grant 13/RC/2106) and co-funded under the European Regional Development Fund.
ID Code:23068
Deposited On:08 Mar 2019 13:02 by Thomas Murtagh . Last Modified 20 Jan 2021 16:40

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