Analyses of computer aided translation typi- cally focus on either frontend interfaces and human effort, or backend translation and machine learnability of corrections. How- ever, this distinction is artificial in prac- tice since the frontend and backend must work in concert. We present the first holis- tic, quantitative evaluation of these issues by contrasting two assistive modes: post- editing and interactive machine translation (MT). We describe a new translator inter- face, extensive modifications to a phrase- based MT system, and a novel objective function for re-tuning to human correc- tions. Evaluation with professional bilin- gual translators shows that post-edit is faster than interactive at the cost of translation quality for French-English and English- German. However, re-tuning the MT sys- tem to interactive output leads to larger, sta- tistically significant reductions in HTER versus re-tuning to post-edit. Analysis shows that tuning directly to HTER results in fine-grained corrections to subsequent machine output.
%0 Journal Article
%1 Green2014
%A Green, Spence
%A Wang, Sida
%A Chuang, Jason
%A Heer, Jeffrey
%A Schuster, Sebastian
%A Manning, Christopher D
%D 2014
%E Moschitti, Alessandro
%E Pang, Bo
%E Daelemans, Walter
%J Empirical Methods in Natural Language Processing (EMNLP)
%K postedición traducción_automática
%P 1225-1236
%R 10.3115/v1/D14-1130
%T Human Effort and Machine Learnability in Computer Aided Translation
%U http://nlp.stanford.edu/pubs/green+wang+chuang+heer+schuster+manning\_emnlp14.pdf
%X Analyses of computer aided translation typi- cally focus on either frontend interfaces and human effort, or backend translation and machine learnability of corrections. How- ever, this distinction is artificial in prac- tice since the frontend and backend must work in concert. We present the first holis- tic, quantitative evaluation of these issues by contrasting two assistive modes: post- editing and interactive machine translation (MT). We describe a new translator inter- face, extensive modifications to a phrase- based MT system, and a novel objective function for re-tuning to human correc- tions. Evaluation with professional bilin- gual translators shows that post-edit is faster than interactive at the cost of translation quality for French-English and English- German. However, re-tuning the MT sys- tem to interactive output leads to larger, sta- tistically significant reductions in HTER versus re-tuning to post-edit. Analysis shows that tuning directly to HTER results in fine-grained corrections to subsequent machine output.
%@ 9781937284961
@article{Green2014,
abstract = {Analyses of computer aided translation typi- cally focus on either frontend interfaces and human effort, or backend translation and machine learnability of corrections. How- ever, this distinction is artificial in prac- tice since the frontend and backend must work in concert. We present the first holis- tic, quantitative evaluation of these issues by contrasting two assistive modes: post- editing and interactive machine translation (MT). We describe a new translator inter- face, extensive modifications to a phrase- based MT system, and a novel objective function for re-tuning to human correc- tions. Evaluation with professional bilin- gual translators shows that post-edit is faster than interactive at the cost of translation quality for French-English and English- German. However, re-tuning the MT sys- tem to interactive output leads to larger, sta- tistically significant reductions in HTER versus re-tuning to post-edit. Analysis shows that tuning directly to HTER results in fine-grained corrections to subsequent machine output.},
added-at = {2017-01-05T16:28:03.000+0100},
author = {Green, Spence and Wang, Sida and Chuang, Jason and Heer, Jeffrey and Schuster, Sebastian and Manning, Christopher D},
biburl = {https://www.bibsonomy.org/bibtex/269c4ede225b86bf5b916743fe5660766/coral.diez},
doi = {10.3115/v1/D14-1130},
editor = {Moschitti, Alessandro and Pang, Bo and Daelemans, Walter},
interhash = {1dcce82f167b0a184c6f00ab52b53c62},
intrahash = {69c4ede225b86bf5b916743fe5660766},
isbn = {9781937284961},
journal = {Empirical Methods in Natural Language Processing (EMNLP)},
keywords = {postedición traducción_automática},
pages = {1225-1236},
timestamp = {2018-05-28T22:04:52.000+0200},
title = {Human Effort and Machine Learnability in Computer Aided Translation},
url = {http://nlp.stanford.edu/pubs/green+wang+chuang+heer+schuster+manning{\_}emnlp14.pdf},
year = 2014
}