%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 }