Article published In:
Translation, Cognition & Behavior
Vol. 4:1 (2021) ► pp.98123
Alves, Favio and Tania Liparini Campos
2009 “Translation Technology In Time: Investigating the impact of translation memory systems and time pressure on types of internal and external support.” In Behind the Mind: Methods, Models and Results in Translation Process Research. Edited by S. Göpferich, A. L. Jakobsen and I. M. Mees. 191–218. Copenhagen: Samfundslitteratur.Google Scholar
Bundgaard, Kristen and Tina P. Christensen
2019 “Is the Concordance Feature the New Black? A workplace study of translators’ interaction with translation resources while post-editing TM and MT matches.” Journal of Specialised Translation, 31 (31): 14–37.Google Scholar
Bürkner, Paul C.
2017 “brms: An R package for Bayesian multilevel models using Stan.” Journal of Statistical Software 80 (1): 1–28. DOI logoGoogle Scholar
Carl, Michael, Barbara Dragsted, Jakob Elming, Daniel Hardt and Arnt L. Jakobsen
2011 “The Process of Post-Editing: A pilot study.” Bernadette Sharp, Michael Zock, Michael Carl, Arnt Lykke Jakobsen. (eds). Proceedings of the 8th International NLPCS Workshop. Special Theme: Human-Machine Interaction in Translation. Copenhagen: Samfundslitteratur, 131–142.Google Scholar
Carl, Michael and Barbara Dragsted
2012 “Inside the Monitor Model: Process of default and challenged translation production.” Translation, Computation, Corpora and Cognition 2 (1): 127–145.Google Scholar
Carl, Michael, Silke Gutermuth and Silvia Hansen-Schirra
2015 “Post-editing Machine Translation: Efficiency, strategies and revision processes in professional translation settings”. In Psycholinguistic and Cognitive Inquiries into Translation and Interpreting. Edited by Aline Ferreira and John Schwieter. 145–174. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Carl, Michael and Moritz Schaeffer
2017a “Why Translation is Difficult: A corpus-based study of non-literality in post-editing and from-scratch translation”. Hermes 561: 43–57. DOI logoGoogle Scholar
2017b “Measuring Translation Literality.” In Translation in Transition. Between Cognition, Computing, and Technology. Edited by Arnt L. Jakobsen and Bartolomé Mesa Lao. 81–105. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Carl, Michael and Cristina Toledo Báez
2019 “Machine Translation Errors and the Translation Process: A study across different languages.” Journal of Specialised Translation, (31), 107–132.Google Scholar
Daems, Joke, Sonia Vandepitte, Robert J. Hartsuiker and Lieve Macken
2017 “Translation Methods and Experience: A comparative analysis of human translation and post-editing with students and professional translators.” Meta 621: 245–270. DOI logoGoogle Scholar
De Groot, Annette M. B.
1992 “Determinants of Word Translation.” Journal of Experimental Psychology: Learning, Memory and Cognition 18 (5): 1001–1018.Google Scholar
Dragsted, Barbara
2010 “Coordination of Reading and Writing Proceses in Translation: An eye on uncharted territory”. In Translation and Cognition. Edited by Gregory M. Shreve and Erik Angelone. 41–62. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Gelman, Andrew, Simpson, Daniel and Michael Betancourt
2017 “The Prior Can Often Only Be Understood in the Context of the Likelihood.” Entropy 19 (10): 1–13. DOI logoGoogle Scholar
Guerberof, Ana
2009 “Productivity and Quality in the Post-Editing of Outputs from Translation Memories and Machine Translation.” The International Journal of Localisation 7 (1): 11–21.Google Scholar
Hatzidaki, Anna
2019 “Using Experimental Approaches to Study Translation: The what and how.” Translation, Cognition & Behavior 2 (1): 35–54. DOI logoGoogle Scholar
2017a “Gravitational Pull in Translation: testing a revised model”. In Empirical Translation Studies: New Methodological and Theoretical Traditions. Edited by Gert De Sutter, Marie-Aude Lefer and Isabelle Delaere. 9–46. Berlin: De Gruyter. DOI logoGoogle Scholar
2017b “Multimethods Approaches.” In Handbook of Translation and Cognition. Edited by John W. Schwieter and Aline Ferreira. 195–212. Hoboken, NJ: Wiley. DOI logoGoogle Scholar
2019 “Default Translation: A construct for Cognitive Translation Studies.” Translation, Cognition & Behavior 2 (2): 187–210. DOI logoGoogle Scholar
Heilmann, Arndt and Stella Neumann
2016 “Dynamic Pause Assessment of Keystroke Logged Data for the Detection of Complexity in transLation and Monolingual Text Production.” In Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), 98–103. Osaka, Japan: The COLING Organizing Committee.Google Scholar
Jakobsen, Arnt L.
1998 “Logging Target Text Production with Translog”. In Probing the Process of Translation: Methods and Results. Edited by Gyde Hansen. 9–20. Copenhagen: Samfundslitteratur.Google Scholar
2002 “Translation Drafting by Professional Translators and by Translation Students.” In Empirical translation studies: Process and Product. Edited by Gyde Hansen. 191–204. Copenhagen: Samfundslitteratur.Google Scholar
Jakobsen, Arnt L. and Kristian T. Jensen
2008 “Eye Movements Behaviour across four Different Types of Reading Task”. Copenhagen Studies in Language 361: 103–124.Google Scholar
Jensen, Kristian Tangsgaard Hvelplund
2011 “Distribution of Attention Between Source Text and Target Text During Translation”. In Cognitive Explorations of Translation. Edited by Sharon O’Brien. 215–238. Continuum: London.Google Scholar
Jia, Yafang, Carl, Michael and Xiangling Wang
2019 “How Does the Post-Editing of Neural Machine Translation Compare with From-Scratch Translation? A product and process-based study”. Jostrans: The Journal of Specialized Translation 311: 60–86.Google Scholar
Jiménez-Crespo, Miguel A. and María Isabel Tercedor Sánchez
Forthcoming. “Explicitation and Implicitation in Translation: Combining comparable and parallel corpus methodologies.” MONTI, Special Issue CTS Spring-cleaning: A Critical Reflexion.
Kruschke, John K.
2018 “Rejecting or Accepting Parameter Values in Bayesian Estimation.” Advances in Methods and Practices in Psychological Science Science 1 (2): 270–280. DOI logoGoogle Scholar
Krings, Hans-Peter
1986Was in den Köpfen von Übersetzern vorgeht. Tübingen: Narr.Google Scholar
2001Repairing Texts: Empirical Investigations of Machine Translation Post-Editing Processes. Ohio: Kent State University PressGoogle Scholar
Kruger, Haidee
2016 “What’s Happening when Nothing’s Happening? Combining eyetracking and keylogging to explore cognitive processing during pauses in translation production.” Across Languages and Cultures 17 (1): 25–52. DOI logoGoogle Scholar
Lacruz, Isabel
2017 “Cognitive Effort in Translation, Editing and Post-Editing.” In Handbook of Translation and Cognition. Edited by John Schwieter and Aline Ferreira. 386–401. Malden, MA: John Wiley & Sons. DOI logoGoogle Scholar
Lacruz, Isabel, Gregory Shreve and Erik Angelone
2012 “Average Pause Ratio as an Indicator of Cognitive Effort in Post-Editing: A case study.” Proceedings of the AMTA 2012 Workshop on Post-editing Technology and Practice. Association for Machine Translation in the Americas, 29–38.Google Scholar
Lacruz, Isabel, Michael Denkowski and Alon Lavie
2014 “Cognitive Demand and Cognitive Effort in Post-Editing”. Paper presented at the 11th Conference of the Association for Machine Translation in the Americas-Third Workshop on Post-Editing Technology and Practice , 22–26 October, 2014, Vancouver BC, Canada.
Lacruz, Isabel and Gregory Shreve
2014“Pauses and Cognitive Effort in Post-editing. In Post-Editing of Machine Translation: Processes and Applications. Edited by Sharon O’Brien, Laura Winther Balling, Michael Carl, Michel Simard, Lucia Specia. 246–274. Cambridge: Cambridge Scholars Publishing.Google Scholar
Langacker, Ronald W.
1987Foundations of Cognitive Linguistics, vol. I, Theorical Prerequisites. Stanford: Stanford University Press.Google Scholar
1991Foundations of Cognitive Linguistics, vol. II, Descriptive Application. Stanford: Stanford University Press.Google Scholar
Leijten, Mariëlle & Luuk Van Waes
2013 “Keystroke Logging in Writing Research: Using Inputlog to analyze writing processes”. Written Communication 30 (3): 358–392. DOI logoGoogle Scholar
Massey, Gary and Maureen Ehrensberger-Dow
2013 “Evaluating Tanslation Processes: Opportunities and challenges”. In New Prospects and Perspectives for Educating Language Mediators. Edited by Don Kiraly, Silvia Hansen-Schirra and Karin Maksymski. 157–180. Tübingen: Gunter Narr.Google Scholar
Mellinger, Christopher
2014Computer-assisted Translation: An Empirical investigation of cognitive effort. Ph.D. dissertation, Kent State University, Kent, OH.Google Scholar
Moorkens, Joss and Andy Way
2016 “Comparing Translator Acceptability of TM and SMT Outputs.” The Baltic Journal of Modern Computing 41: 141–151.Google Scholar
Muñoz Martín, Ricardo
2014 “A Blurred Snapshot of Advances in Translation Process Research.” MonTI Special Issue-Minding Translation: 49–84.Google Scholar
Muñoz Martín, Ricardo and Jose M. Cardona Guerra
2018 “Translating in Fits and Starts: Pause thresholds and roles in the research of translation processes.” Perspectives: Studies in Translatology. DOI logoGoogle Scholar
Muñoz Martín, Ricardo and Kairong Xiao
(Eds.) 2020 “Cognitive Translation Studies: Theoretical models and methodological criticism.” Linguistica Antverpiensia, New Series-Themes in Translation Studies, 191.Google Scholar
O’Brien, Sharon
2006 “Pauses as Indicators of Cognitive Effort in Post-Editing Machine Translation Output.” Across Languages and Cultures 7 (1): 1–21. DOI logoGoogle Scholar
2007 “An Empirical Investigation of Temporal and Technical Post-Editing Effort.” Translation and Interpreting Studies: 83–136. DOI logoGoogle Scholar
2008 “Processing Fuzzy Matches in Translation Memory Tools: An eye tracking analysis.” In Looking at Eyes: Eye-Tracking Studies of Reading and Translation Processing. Edited by Susanne Göpferich, Arnt Lykke Jakobsen, and Inger M. Mees. 79–102. Copenhagen: Samfundslitteratur 2008.Google Scholar
R Core Team
2018R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from [URL]
Schaeffer, Moritz and Michael Carl
2013 “Shared Representations of the Translation Process: A recursive model.” Translation and Interpreting Studies 8 (2): 169–190. DOI logoGoogle Scholar
2014 “Measuring the Cognitive Effort of Literal Translation Processes.” Workshop on Human and Computer-assisted Translation, 29–37. Gothenburg, Sweden: Association for Computational Linguistics. DOI logoGoogle Scholar
Screen, Benjamin
2018 “What Effect Does Post-Editing Have on the Translation Product from an End-User’s Perspective?Jostrans 311: 133–157.Google Scholar
Stan Development Team
2018Stan Modeling Language Users Guide and Reference Manual (Version 2.18.0). Stan Development Team. Retrieved from [URL]
Tirkkonen-Condit, Sonja
2005 “The Monitor Model Revisited: Evidence from process research.” META 50 (2): 405–414. DOI logoGoogle Scholar
Tirkkonen-Condit, Sonja, Jukka Mäkisalo and Sini Immonen
2008 “The Translation Process-Interplay between literal rendering and a search for sense.” Across Languages and Cultures 9 (1): 1–17. DOI logoGoogle Scholar
Vandepitte, Sonia, Hartsuiker, Robert J. and Eva Van Assche
2015 “Process and Text Studies of a Translation Problem”. In Psycholinguistic and Cognitive Inquiries into Translation and Interpreting. Edited by Aline Ferreira, and John W. Schwieter. 127–143. Philadelphia: John Benjamins. DOI logoGoogle Scholar