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Bilingual Embeddings and Word Alignments for Translation Quality Estimation

Article scientifique 2016 Anglais

Résumé

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.

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Abdelsalam, A., Bojar, O., El-Beltagy, S. (2016). Bilingual Embeddings and Word Alignments for Translation Quality Estimation. https://doi.org/10.18653/v1/w16-2380

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Auteur(s)

Amal Abdelsalam Ondřej Bojar Samhaa R. El-Beltagy

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