@inproceedings{lacruz-etal-2014-cognitive,
title = "Cognitive demand and cognitive effort in post-editing",
author = "Lacruz, Isabel and
Denkowski, Michael and
Lavie, Alon",
editor = "O'Brien, Sharon and
Simard, Michel and
Specia, Lucia",
booktitle = "Proceedings of the 11th Conference of the Association for Machine Translation in the Americas",
month = oct # " 22-26",
year = "2014",
address = "Vancouver, Canada",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2014.amta-wptp.6",
pages = "73--84",
abstract = "The pause to word ratio, the number of pauses per word in a post-edited MT segment, is an indicator of cognitive effort in post-editing (Lacruz and Shreve, 2014). We investigate how low the pause threshold can reasonably be taken, and we propose that 300 ms is a good choice, as pioneered by Schilperoord (1996). We then seek to identify a good measure of the cognitive demand imposed by MT output on the post-editor, as opposed to the cognitive effort actually exerted by the post-editor during post-editing. Measuring cognitive demand is closely related to measuring MT utility, the MT quality as perceived by the post-editor. HTER, an extrinsic edit to word ratio that does not necessarily correspond to actual edits per word performed by the post-editor, is a well-established measure of MT quality, but it does not comprehensively capture cognitive demand (Koponen, 2012). We investigate intrinsic measures of MT quality, and so of cognitive demand, through edited-error to word metrics. We find that the transfer-error to word ratio predicts cognitive effort better than mechanical-error to word ratio (Koby and Champe, 2013). We identify specific categories of cognitively challenging MT errors whose error to word ratios correlate well with cognitive effort.",
}
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<abstract>The pause to word ratio, the number of pauses per word in a post-edited MT segment, is an indicator of cognitive effort in post-editing (Lacruz and Shreve, 2014). We investigate how low the pause threshold can reasonably be taken, and we propose that 300 ms is a good choice, as pioneered by Schilperoord (1996). We then seek to identify a good measure of the cognitive demand imposed by MT output on the post-editor, as opposed to the cognitive effort actually exerted by the post-editor during post-editing. Measuring cognitive demand is closely related to measuring MT utility, the MT quality as perceived by the post-editor. HTER, an extrinsic edit to word ratio that does not necessarily correspond to actual edits per word performed by the post-editor, is a well-established measure of MT quality, but it does not comprehensively capture cognitive demand (Koponen, 2012). We investigate intrinsic measures of MT quality, and so of cognitive demand, through edited-error to word metrics. We find that the transfer-error to word ratio predicts cognitive effort better than mechanical-error to word ratio (Koby and Champe, 2013). We identify specific categories of cognitively challenging MT errors whose error to word ratios correlate well with cognitive effort.</abstract>
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%0 Conference Proceedings
%T Cognitive demand and cognitive effort in post-editing
%A Lacruz, Isabel
%A Denkowski, Michael
%A Lavie, Alon
%Y O’Brien, Sharon
%Y Simard, Michel
%Y Specia, Lucia
%S Proceedings of the 11th Conference of the Association for Machine Translation in the Americas
%D 2014
%8 oct 22 26
%I Association for Machine Translation in the Americas
%C Vancouver, Canada
%F lacruz-etal-2014-cognitive
%X The pause to word ratio, the number of pauses per word in a post-edited MT segment, is an indicator of cognitive effort in post-editing (Lacruz and Shreve, 2014). We investigate how low the pause threshold can reasonably be taken, and we propose that 300 ms is a good choice, as pioneered by Schilperoord (1996). We then seek to identify a good measure of the cognitive demand imposed by MT output on the post-editor, as opposed to the cognitive effort actually exerted by the post-editor during post-editing. Measuring cognitive demand is closely related to measuring MT utility, the MT quality as perceived by the post-editor. HTER, an extrinsic edit to word ratio that does not necessarily correspond to actual edits per word performed by the post-editor, is a well-established measure of MT quality, but it does not comprehensively capture cognitive demand (Koponen, 2012). We investigate intrinsic measures of MT quality, and so of cognitive demand, through edited-error to word metrics. We find that the transfer-error to word ratio predicts cognitive effort better than mechanical-error to word ratio (Koby and Champe, 2013). We identify specific categories of cognitively challenging MT errors whose error to word ratios correlate well with cognitive effort.
%U https://aclanthology.org/2014.amta-wptp.6
%P 73-84
Markdown (Informal)
[Cognitive demand and cognitive effort in post-editing](https://aclanthology.org/2014.amta-wptp.6) (Lacruz et al., AMTA 2014)
ACL
- Isabel Lacruz, Michael Denkowski, and Alon Lavie. 2014. Cognitive demand and cognitive effort in post-editing. In Proceedings of the 11th Conference of the Association for Machine Translation in the Americas, pages 73–84, Vancouver, Canada. Association for Machine Translation in the Americas.