LORIA System for the WMT15 Quality Estimation Shared Task
David Langlois · 2015
We describe our system for WMT2015 Shared Task on Quality Estimation, task 1, sentence-level prediction of post-edition effort.We use baseline features, Latent Semantic Indexing based features and features based on pseudo-references.SVM algorithm allows to estimate the linear regression between the features vectors and the HTER score.We use a selection algorithm in order to put aside needless features.Our best system leads to a performance in terms of Mean Absolute Error equal to 13.34 on official test while the official baseline system leads to a performance equal to 14.82.