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Translation dictation vs. post-editing with cloud-based voice recognition: a pilot experiment
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In: 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. (2017)
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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.
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Keyword:
Machine translating
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URL: http://doras.dcu.ie/23068/
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Translating On the Go? Investigating the Potential of Multimodal Mobile Devices for Interactive Translation Dictation
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In: Tradumàtica: traducció i tecnologies de la informació i la comunicació; Núm. 14 (2016): Traducció i dispositius mòbils; p. 66-74 (2016)
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