Bilingual Embeddings and Word Alignments for Translation Quality Estimation
Amal Abdelsalam, Ondřej Bojar, Samhaa R. El-Beltagy · 2016
This paper describes our submission UFAL MULTIVEC to the WMT16 Quality Estimation Shared Task, for English-German sentence-level post-editing effort prediction and ranking.Our approach exploits the power of bilingual distributed representations, word alignments and also manual post-edits to boost the performance of the baseline QuEst++ set of features.Our model outperforms the baseline, as well as the winning system in WMT15, Referential Translation Machines (RTM), in both scoring and ranking sub-tasks.