@inproceedings{he-etal-2010-improving,
title = "Improving the Post-Editing Experience using Translation Recommendation: A User Study",
author = "He, Yifan and
Ma, Yanjun and
Roturier, Johann and
Way, Andy and
van Genabith, Josef",
booktitle = "Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers",
month = oct # " 31-" # nov # " 4",
year = "2010",
address = "Denver, Colorado, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2010.amta-papers.27",
abstract = "We report findings from a user study with professional post-editors using a translation recommendation framework (He et al., 2010) to integrate Statistical Machine Translation (SMT) output with Translation Memory (TM) systems. The framework recommends SMT outputs to a TM user when it predicts that SMT outputs are more suitable for post-editing than the hits provided by the TM. We analyze the effectiveness of the model as well as the reaction of potential users. Based on the performance statistics and the users{'} comments, we find that translation recommendation can reduce the workload of professional post-editors and improve the acceptance of MT in the localization industry.",
}
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<abstract>We report findings from a user study with professional post-editors using a translation recommendation framework (He et al., 2010) to integrate Statistical Machine Translation (SMT) output with Translation Memory (TM) systems. The framework recommends SMT outputs to a TM user when it predicts that SMT outputs are more suitable for post-editing than the hits provided by the TM. We analyze the effectiveness of the model as well as the reaction of potential users. Based on the performance statistics and the users’ comments, we find that translation recommendation can reduce the workload of professional post-editors and improve the acceptance of MT in the localization industry.</abstract>
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%0 Conference Proceedings
%T Improving the Post-Editing Experience using Translation Recommendation: A User Study
%A He, Yifan
%A Ma, Yanjun
%A Roturier, Johann
%A Way, Andy
%A van Genabith, Josef
%S Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2010
%8 oct 31 nov 4
%I Association for Machine Translation in the Americas
%C Denver, Colorado, USA
%F he-etal-2010-improving
%X We report findings from a user study with professional post-editors using a translation recommendation framework (He et al., 2010) to integrate Statistical Machine Translation (SMT) output with Translation Memory (TM) systems. The framework recommends SMT outputs to a TM user when it predicts that SMT outputs are more suitable for post-editing than the hits provided by the TM. We analyze the effectiveness of the model as well as the reaction of potential users. Based on the performance statistics and the users’ comments, we find that translation recommendation can reduce the workload of professional post-editors and improve the acceptance of MT in the localization industry.
%U https://aclanthology.org/2010.amta-papers.27
Markdown (Informal)
[Improving the Post-Editing Experience using Translation Recommendation: A User Study](https://aclanthology.org/2010.amta-papers.27) (He et al., AMTA 2010)
ACL