@inproceedings{sanchez-torron-koehn-2016-machine,
title = "Machine Translation Quality and Post-Editor Productivity",
author = "Sanchez-Torron, Marina and
Koehn, Philipp",
editor = "Green, Spence and
Schwartz, Lane",
booktitle = "Conferences of the Association for Machine Translation in the Americas: MT Researchers' Track",
month = oct # " 28 - " # nov # " 1",
year = "2016",
address = "Austin, TX, USA",
publisher = "The Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2016.amta-researchers.2",
pages = "16--26",
abstract = "We assessed how different machine translation (MT) systems affect the post-editing (PE) process and product of professional English{--}Spanish translators. Our model found that for each 1-point increase in BLEU, there is a PE time decrease of 0.16 seconds per word, about 3-4{\%}. The MT system with the lowest BLEU score produced the output that was post-edited to the lowest quality and with the highest PE effort, measured both in HTER and actual PE operations.",
}
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<abstract>We assessed how different machine translation (MT) systems affect the post-editing (PE) process and product of professional English–Spanish translators. Our model found that for each 1-point increase in BLEU, there is a PE time decrease of 0.16 seconds per word, about 3-4%. The MT system with the lowest BLEU score produced the output that was post-edited to the lowest quality and with the highest PE effort, measured both in HTER and actual PE operations.</abstract>
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%0 Conference Proceedings
%T Machine Translation Quality and Post-Editor Productivity
%A Sanchez-Torron, Marina
%A Koehn, Philipp
%Y Green, Spence
%Y Schwartz, Lane
%S Conferences of the Association for Machine Translation in the Americas: MT Researchers’ Track
%D 2016
%8 oct 28 nov 1
%I The Association for Machine Translation in the Americas
%C Austin, TX, USA
%F sanchez-torron-koehn-2016-machine
%X We assessed how different machine translation (MT) systems affect the post-editing (PE) process and product of professional English–Spanish translators. Our model found that for each 1-point increase in BLEU, there is a PE time decrease of 0.16 seconds per word, about 3-4%. The MT system with the lowest BLEU score produced the output that was post-edited to the lowest quality and with the highest PE effort, measured both in HTER and actual PE operations.
%U https://aclanthology.org/2016.amta-researchers.2
%P 16-26
Markdown (Informal)
[Machine Translation Quality and Post-Editor Productivity](https://aclanthology.org/2016.amta-researchers.2) (Sanchez-Torron & Koehn, AMTA 2016)
ACL
- Marina Sanchez-Torron and Philipp Koehn. 2016. Machine Translation Quality and Post-Editor Productivity. In Conferences of the Association for Machine Translation in the Americas: MT Researchers' Track, pages 16–26, Austin, TX, USA. The Association for Machine Translation in the Americas.