YSDA Participation in the WMT'16 Quality Estimation Shared Task

Abstract

This paper describes Yandex School of Data Analysis (YSDA) submission for WMT2016 Shared Task on Quality Estimation (QE) / Task 1: Sentence-level prediction of post-editing effort. We solve the problem of quality estimation by using a machine learning approach, where we try to learn a regressor from feature space to HTER score. By enriching the baseline features with the syntactical features and additional translation system based features, we achieve Pearson correlation of 0.525 on the test set.