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Testing interaction with a mobile MT postediting app

Torres-Hostench, Olga ORCID: 0000-0003-1525-0304, Moorkens, Joss ORCID: 0000-0003-0766-0071, O'Brien, Sharon ORCID: 0000-0003-4864-5986 and Vreeke, Joris ORCID: 0000-0003-3810-7631 (2017) Testing interaction with a mobile MT postediting app. Translation and Interpreting : the International Journal of Translation and Interpreting Research, 9 (2). pp. 138-150. ISSN 1836-9324

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Abstract

Kanjingo is a post-editing application for iOS devices developed at the ADAPT Centre (formerly CNGL) at Dublin City University (DCU). The first stage of user testing was conducted in 2014 (reported in O’Brien, Moorkens & Vreeke, 2014), and improvements were made based on the initial feedback. This abstract describes further exploratory testing based on the second iteration of the Kanjingo application. The new tests were designed with several aims: (1) testing Kanjingo for post-editing using the phone’s keyboard (2) testing Kanjingo for post-editing with voice input; (3) testing Kanjingo for revision of post-edited texts; (4) testing Kanjingo general usability; and (5) testing Kanjingo interface design. This paper presents the results of the various tests, issues identified, and ideas for improvements. For example, the use of Kanjingo for post-editing with voice input, one of the most innovative forms of interaction with MT in the test, worked much better than participants expected, and this mode of input was preferred for translating from scratch when MT quality was very poor, whereas post-editing short words or phrases was found to be faster with the iPhone keyboard. In addition, we present some reflections on the strengths and weaknesses of the testing methods employed.

Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:machine translation post-editing; mobile devices; Kanjingo; mobile app;
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
Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Publisher:Western Sydney University
Official URL:http://dx.doi.org/10.12807/ti.109202.2017.a09
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:ProjecTA project “Translation projects with Statistical Machine Translation and Postediting”, grant number FFI2013- 46041-R [MINECO / FEDER, UE], ADAPT Centre for Digital Content Technology, funded under the SFI Research Centres Programme (Grant 13/RC/2106) and co-funded under the European Regional Development Fund.
ID Code:23295
Deposited On:13 May 2019 15:32 by Thomas Murtagh . Last Modified 15 May 2019 15:58

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