E.g., 07/16/2020
E.g., 07/16/2020
Free for GALA Members
$60.00 for Non-Members


Stephen Doherty and Federico Gaspari from the Centre for Next Generation Localization at Dublin City University give an overview of post-editing and discuss when to use post-editing and when not to. As a relatively recent addition to the translation and localization professional’s toolkit, post-editing is becoming a more substantiated and explored field both within research and industrial contexts. However, with the exception of few specialized training courses, knowledge and application of post-editing is not as widespread as it could be given its potential for resource saving. While its demonstrated market growth is becoming apparent (e.g. Common Sense Advisory: The Language Services Market, 2012, 2013), knowing when, how, and why post-editing is the best option has become a valuable and transferable skill. The presenters give a critical overview of post-editing, describe post-editing scenarios including gisting and high-quality dissemination, advise on how to modify post-editing strategies for different machine translation systems, and provide practical knowledge to know when to use post-editing and when not to.

Federico Gaspari

Federico Gaspari has a background in translation studies and holds a PhD in machine translation from the University of Manchester. He has more than 10 years’ experience as a university lecturer in specialized translation and translation technology in Italy and the UK. He is a postdoctoral researcher at the Centre for Next Generation Localisation at Dublin City University, specializing in translation quality evaluation as part of the QTLaunchPad project.

Stephen Doherty

Stephen Doherty, BA, HDip, PhD, MBPsS, is a post-doctoral researcher in the Centre for Next Generation Localisation in Dublin City University. He conducts research on topics of language and cognition, human-computer interaction, machine translation, and translation technologies. He is currently working on QTLaunchPad, a collaborative European research initiative dedicated to overcoming barriers in machine translation and language technologies.