%0 Journal Article %1 Vieira2014 %A Vieira, Lucas Nunes %D 2014 %J Machine Translation %K postedición traducción_automática %N 3-4 %P 187-216 %R 10.1007/s10590-014-9156-x %T Indices of cognitive effort in machine translation post-editing %U http://link.springer.com/article/10.1007\%2Fs10590-014-9156-x %V 28 %X Identifying indices of effort in post-editing of machine translation can have a number of applications, including estimating machine translation quality and calculating post-editors' pay rates. Both source-text and machine-output features as well as subjects' traits are investigated here in view of their impact on cognitive effort, which is measured with eye tracking and a subjective scale borrowed from the field of Educational Psychology. Data is analysed with mixed-effects models, and results indicate that the semantics-based automatic evaluation metric Meteor is significantly correlated with all measures of cognitive effort considered. Smaller effects are also observed for source-text linguistic features. Further insight is provided into the role of the source text in post-editing, with results suggesting that consulting the source text is only associated with how cognitively demanding the task is perceived in the case of those with a low level of proficiency in the source language. Subjects' working memory capacity was also taken into account and a relationship with post-editing productivity could be noticed. Scaled-up studies into the construct of working memory capacity and the use of eye tracking in models for quality estimation are suggested as future work. %@ 0922-6567

@article{Vieira2014, abstract = {Identifying indices of effort in post-editing of machine translation can have a number of applications, including estimating machine translation quality and calculating post-editors' pay rates. Both source-text and machine-output features as well as subjects' traits are investigated here in view of their impact on cognitive effort, which is measured with eye tracking and a subjective scale borrowed from the field of Educational Psychology. Data is analysed with mixed-effects models, and results indicate that the semantics-based automatic evaluation metric Meteor is significantly correlated with all measures of cognitive effort considered. Smaller effects are also observed for source-text linguistic features. Further insight is provided into the role of the source text in post-editing, with results suggesting that consulting the source text is only associated with how cognitively demanding the task is perceived in the case of those with a low level of proficiency in the source language. Subjects' working memory capacity was also taken into account and a relationship with post-editing productivity could be noticed. Scaled-up studies into the construct of working memory capacity and the use of eye tracking in models for quality estimation are suggested as future work.}, added-at = {2017-01-05T16:28:03.000+0100}, author = {Vieira, Lucas Nunes}, biburl = {https://www.bibsonomy.org/bibtex/2001511655a52c9aeff8262de6df8a3e0/coral.diez}, doi = {10.1007/s10590-014-9156-x}, interhash = {a2103c8edd52022310619493535a244c}, intrahash = {001511655a52c9aeff8262de6df8a3e0}, isbn = {0922-6567}, journal = {Machine Translation}, keywords = {postedición traducción_automática}, number = {3-4}, pages = {187-216}, timestamp = {2018-05-28T22:02:20.000+0200}, title = {Indices of cognitive effort in machine translation post-editing}, url = {http://link.springer.com/article/10.1007{\%}2Fs10590-014-9156-x}, volume = 28, year = 2014 }