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
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.
Metadata
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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