Joint Training for Neural Machine Translation Models with Monolingual Data

1 Mar 2018Zhirui ZhangShujie LiuMu LiMing ZhouEnhong Chen

Monolingual data have been demonstrated to be helpful in improving translation quality of both statistical machine translation (SMT) systems and neural machine translation (NMT) systems, especially in resource-poor or domain adaptation tasks where parallel data are not rich enough. In this paper, we propose a novel approach to better leveraging monolingual data for neural machine translation by jointly learning source-to-target and target-to-source NMT models for a language pair with a joint EM optimization method... (read more)

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