Cover not available

Article published In: Translation, Cognition & Behavior
Vol. 4:1 (2021) ► pp.98123

Get fulltext from our e-platform
References (55)
References
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 logo with link to 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 logo with link to Google Scholar
Bürkner, Paul C. 2017. “brms: An R package for Bayesian multilevel models using Stan.” Journal of Statistical Software 80 (1): 1–28. Google Scholar logo with link to Google 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 logo with link to 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 logo with link to 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. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google 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 logo with link to 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. Google Scholar logo with link to Google 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 logo with link to 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. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google 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 logo with link to Google Scholar
Hatzidaki, Anna. 2019. “Using Experimental Approaches to Study Translation: The what and how.” Translation, Cognition & Behavior 2 (1): 35–54. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google Scholar
. 2017b. “Multimethods Approaches.” In Handbook of Translation and Cognition. Edited by John W. Schwieter and Aline Ferreira. 195–212. Hoboken, NJ: Wiley. Google Scholar logo with link to Google Scholar
. 2019. “Default Translation: A construct for Cognitive Translation Studies.” Translation, Cognition & Behavior 2 (2): 187–210. Google Scholar logo with link to Google 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 logo with link to 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 logo with link to 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 logo with link to 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 logo with link to 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 logo with link to 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 logo with link to Google Scholar
Jiménez-Crespo, Miguel A. and María Isabel Tercedor Sánchez. 2017. “Lexical Variation, Register and Explicitation in Medical Translation: A comparable corpus study of medical terminology in US websites translated into Spanish”. TIS: Translation and Interpreting Studies 12 (3): 405–426. Google Scholar logo with link to Google Scholar
. 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. Google Scholar logo with link to Google Scholar
Krings, Hans-Peter. 1986. Was in den Köpfen von Übersetzern vorgeht. Tübingen: Narr.Google Scholar logo with link to Google Scholar
. 2001. Repairing Texts: Empirical Investigations of Machine Translation Post-Editing Processes. Ohio: Kent State University PressGoogle Scholar logo with link to Google 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. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google 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 logo with link to 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 logo with link to Google Scholar
Langacker, Ronald W. 1987. Foundations of Cognitive Linguistics, vol. I, Theorical Prerequisites. Stanford: Stanford University Press.Google Scholar logo with link to Google Scholar
1991. Foundations of Cognitive Linguistics, vol. II, Descriptive Application. Stanford: Stanford University Press.Google Scholar logo with link to 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. Google Scholar logo with link to Google 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 logo with link to Google Scholar
Mellinger, Christopher. 2014. Computer-assisted Translation: An Empirical investigation of cognitive effort. Ph.D. dissertation, Kent State University, Kent, OH.Google Scholar logo with link to 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 logo with link to Google Scholar
Muñoz Martín, Ricardo. 2014. “A Blurred Snapshot of Advances in Translation Process Research.” MonTI Special Issue-Minding Translation: 49–84.Google Scholar logo with link to 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. Google Scholar logo with link to Google 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 logo with link to 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. Google Scholar logo with link to Google Scholar
. 2007. “An Empirical Investigation of Temporal and Technical Post-Editing Effort.” Translation and Interpreting Studies: 83–136. Google Scholar logo with link to Google 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 logo with link to Google Scholar
R Core Team. 2018. R: 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. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google 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 logo with link to Google Scholar
Stan Development Team. 2018. Stan 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. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google 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. Google Scholar logo with link to Google Scholar
Cited by (4)

Cited by four other publications

Hegrenæs, Claudia Förster & Sandra Louise Halverson
2025. What characterizes default translations? Exploring the default translation hypothesis. Perspectives  pp. 1 ff. DOI logo
Lahiani, Raja
2025. Smurfing beyond translation. Translation Spaces DOI logo
Martín, Ricardo Muñoz, Sanjun Sun, Zhiqiang Du & Sara Puerini
2025. Keylogging. In Research Methods in Cognitive Translation and Interpreting Studies [Research Methods in Applied Linguistics, 10],  pp. 157 ff. DOI logo
ROJO LÓPEZ, ANA MARÍA, María Inmaculada Vicente López & Kristian Tangsgaard Hvelplund
2024. Measuring cognitive effort in post-editing: an eye-tracking study comparing professional and student translators. Tradumàtica tecnologies de la traducció :22  pp. 112 ff. DOI logo

This list is based on CrossRef data as of 5 december 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

Mobile Menu Logo with link to supplementary files background Layer 1 prag Twitter_Logo_Blue