Target-Centric Features for Translation Quality Estimation

摘要

We describe the DCU-MIXED and DCU-SVR submissions to the WMT-14 Quality Estimation task 1.1, predicting sentence-level perceived post-editing effort. Feature design focuses on target-side features as we hypothesise that the source side has little effect on the quality of human translations, which are included in task 1.1 of this year's WMT Quality Estimation shared task. We experiment with features of the QuEst framework, features of our past work, and three novel feature sets. Despite these efforts, our two systems perform poorly in the competition. Follow up experiments indicate that the poor performance is due to improperly optimised parameters.