The SDL Language Weaver Systems in the WMT12 Quality Estimation Shared Task

Abstract

We present in this paper the system submissions of the SDL Language Weaver team in the WMT 2012 Quality Estimation shared-task. Our MT quality-prediction systems use machine learning techniques (M5P regression-tree and SVM-regression models) and a feature-selection algorithm that has been designed to directly optimize towards the official metrics used in this shared-task. The resulting submissions placed 1st (the M5P model) and 2nd (the SVM model), respectively, on both the Ranking task and the Scoring task, out of 11 participating teams. 1