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Monolingually Derived Phrase Scores for Phrase Based SMT Using Neural Networks Vector Representations
[article]
2016
arXiv
pre-print
In this paper, we propose two new features for estimating phrase-based machine translation parameters from mainly monolingual data. Our method is based on two recently introduced neural network vector representation models for words and sentences. It is the first time that these models have been used in an end to end phrase-based machine translation system. Scores obtained from our method can recover more than 80% of BLEU loss caused by removing phrase table probabilities. We also show that our
arXiv:1506.00406v3
fatcat:5x4chtbbargxbpprncx62v6brq