Translation Quality Estimation using Recurrent Neural Network

Understand

This paper describes our submission to the shared task on word/phrase level Quality Estimation (QE) in the First Conference on Statistical Machine Translation (WMT16).

• The objective of the shared task was to predict if the given word/phrase is a correct/incorrect (OK/BAD) translation in the given sentence.
• In this paper, we propose a novel approach for word level Quality Estimation using Recurrent Neural Network Language Model (RNN-LM) architecture.
• RNN-LMs have been found very effective in different Natural Language Processing (NLP) applications.