A user study of neural interactive translation prediction

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dc.contributor.author Knowles, Rebecca en
dc.contributor.author Sanchez Torron, Marina en
dc.contributor.author Koehn, Philipp en
dc.date.accessioned 2019-05-28T21:30:08Z en
dc.date.issued 2019-05-02 en
dc.identifier.issn 1573-0573 en
dc.identifier.uri http://hdl.handle.net/2292/46821 en
dc.description.abstract Machine translation (MT) on its own is generally not good enough to produce high-quality translations, so it is common to have humans intervening in the translation process to improve MT output. A typical intervention is post-editing (PE), where a human translator corrects errors in the MT output. Another is interactive translation prediction (ITP), which involves an MT system presenting a translator with translation suggestions they can accept or reject, actions the MT system then uses to present them with new, corrected suggestions. Both Macklovitch (2006) and Koehn (2009) found ITP to be an efficient alternative to unassisted translation in terms of processing time. So far, phrase-based statistical ITP has not yet proven to be faster than PE (Koehn 2009; Sanchis-Trilles et al. 2014; Underwood et al. 2014; Green et al. 2014; Alves et al. 2016; Alabau et al. 2016). In this paper we present the results of an empirical study on translation productivity in ITP with an underlying neural MT system (NITP). Our results show that over half of the professional translators in our study translated faster with NITP compared to PE, and most preferred it over PE. We also examine differences between PE and ITP in other translation productivity indicators and translators’ reactions to the technology. en
dc.relation.ispartofseries Machine Translation en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title A user study of neural interactive translation prediction en
dc.type Journal Article en
dc.identifier.doi 10.1007/s10590-019-09235-8 en
dc.rights.holder Copyright: The author en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype article en
pubs.elements-id 770344 en
pubs.record-created-at-source-date 2019-05-08 en


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