@inproceedings{singla-etal-2014-predicting,
title = "Predicting post-editor profiles from the translation process",
author = "Singla, Karan and
Orrego-Carmona, David and
Gonzales, Ashleigh Rhea and
Carl, Michael and
Bangalore, Srinivas",
editor = "Casacuberta, Francisco and
Federico, Marcello and
Koehn, Philipp",
booktitle = "Workshop on interactive and adaptive machine translation",
month = oct # " 22",
year = "2014",
address = "Vancouver, Canada",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2014.amta-workshop.6",
pages = "51--60",
abstract = "The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT Translation Process Research Database (TPR-DB). The analysis has two main research goals: We create n-gram models based on user activity and part-of-speech sequences to automatically cluster post-editors, and we use discriminative classifier models to characterize post-editors based on a diverse range of translation process features. The classification and clustering of participants resulting from our study suggest this type of exploration could be used as a tool to develop new translation tool features or customization possibilities.",
}
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<abstract>The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT Translation Process Research Database (TPR-DB). The analysis has two main research goals: We create n-gram models based on user activity and part-of-speech sequences to automatically cluster post-editors, and we use discriminative classifier models to characterize post-editors based on a diverse range of translation process features. The classification and clustering of participants resulting from our study suggest this type of exploration could be used as a tool to develop new translation tool features or customization possibilities.</abstract>
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%0 Conference Proceedings
%T Predicting post-editor profiles from the translation process
%A Singla, Karan
%A Orrego-Carmona, David
%A Gonzales, Ashleigh Rhea
%A Carl, Michael
%A Bangalore, Srinivas
%Y Casacuberta, Francisco
%Y Federico, Marcello
%Y Koehn, Philipp
%S Workshop on interactive and adaptive machine translation
%D 2014
%8 oct 22
%I Association for Machine Translation in the Americas
%C Vancouver, Canada
%F singla-etal-2014-predicting
%X The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT Translation Process Research Database (TPR-DB). The analysis has two main research goals: We create n-gram models based on user activity and part-of-speech sequences to automatically cluster post-editors, and we use discriminative classifier models to characterize post-editors based on a diverse range of translation process features. The classification and clustering of participants resulting from our study suggest this type of exploration could be used as a tool to develop new translation tool features or customization possibilities.
%U https://aclanthology.org/2014.amta-workshop.6
%P 51-60
Markdown (Informal)
[Predicting post-editor profiles from the translation process](https://aclanthology.org/2014.amta-workshop.6) (Singla et al., AMTA 2014)
ACL
- Karan Singla, David Orrego-Carmona, Ashleigh Rhea Gonzales, Michael Carl, and Srinivas Bangalore. 2014. Predicting post-editor profiles from the translation process. In Workshop on interactive and adaptive machine translation, pages 51–60, Vancouver, Canada. Association for Machine Translation in the Americas.