Is Neural Machine Translation the New State of the Art? AW Sheila Castilho, Joss Moorkens, Federico Gaspari, Iacer Calixto, John Tinsley Prague Bulletin of Mathematical Linguistics, 109-120, 2017 | 313* | 2017 |
Approaches to human and machine translation quality assessment S Castilho, S Doherty, F Gaspari, J Moorkens Translation quality assessment: From principles to practice, 9-38, 2018 | 171 | 2018 |
Under pressure: translation in times of austerity J Moorkens Perspectives 25 (3), 464-477, 2017 | 157 | 2017 |
Machine translation and post-editing training as part of a master’s programme A Guerberof Arenas, J Moorkens Jostrans: The Journal of Specialised Translation, 217-238, 2019 | 152 | 2019 |
Assessing user interface needs of post-editors of machine translation J Moorkens, S O’Brien Human Issues in Translation Technology: The IATIS Yearbook, 109, 2017 | 148 | 2017 |
Translators’ perceptions of literary post-editing using statistical and neural machine translation J Moorkens, A Toral, S Castilho, A Way Translation Spaces 7 (2), 240-262, 2018 | 136 | 2018 |
What to expect from Neural Machine Translation: a practical in-class translation evaluation exercise J Moorkens The Interpreter and Translator Trainer 12 (4), 375-387, 2018 | 123 | 2018 |
A comparative quality evaluation of PBSMT and NMT using professional translators S Castilho, J Moorkens, F Gaspari, R Sennrich, V Sosoni, ... Proceedings of Machine Translation Summit XVI: Research Track, 116-131, 2017 | 117 | 2017 |
Translation quality assessment J Moorkens, S Castilho, F Gaspari, S Doherty Machine translation: Technologies and applications ser. Cham: Springer …, 2018 | 111 | 2018 |
Correlations of perceived post-editing effort with measurements of actual effort J Moorkens, S O’brien, IAL Da Silva, NB de Lima Fonseca, F Alves Machine Translation 29, 267-284, 2015 | 95 | 2015 |
Investigating the experience of translation technology labs: pedagogical implications S Doherty, J Moorkens The Journal of Specialised Translation, 122-136, 2013 | 93 | 2013 |
“A tiny cog in a large machine” Digital Taylorism in the translation industry J Moorkens Translation Spaces 9 (1), 12-34, 2020 | 91 | 2020 |
Post-editing evaluations: Trade-offs between novice and professional participants J Moorkens, S O’Brien Proceedings of the 18th annual conference of the European association for …, 2015 | 79 | 2015 |
Post-editing neural machine translation versus translation memory segments P Sánchez-Gijón, J Moorkens, A Way Machine Translation 33 (1), 31-59, 2019 | 61 | 2019 |
Ethics and machine translation J Moorkens Machine translation for everyone: Empowering users in the age of artificial …, 2022 | 58 | 2022 |
Copyright and the re-use of translation as data J Moorkens, D Lewis The Routledge handbook of translation and technology, 469-481, 2019 | 48 | 2019 |
Towards intelligent post-editing interfaces S O'Brien, J Moorkens BDU Fachverlag, 2014 | 48 | 2014 |
User Attitudes to the Post-Editing Interface J Moorkens, S O’Brien Machine Translation Summit XIV, 19, 2013 | 48 | 2013 |
Differentiating editing, post-editing and revision F Do Carmo, J Moorkens Translation revision and post-editing, 35-49, 2020 | 47 | 2020 |
Evaluating MT for massive open online courses: A multifaceted comparison between PBSMT and NMT systems S Castilho, J Moorkens, F Gaspari, R Sennrich, A Way, ... Machine translation 32 (3), 255-278, 2018 | 46 | 2018 |