Paper: Human Effort and Machine Learnability in Computer Aided Translation

ACL ID D14-1130
Title Human Effort and Machine Learnability in Computer Aided Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

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-tuni...