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Prior Knowledge Integration for Neural Machine Translation using
Posterior Regularization
release_za4zbk7mwva4fem7frhl7roijq
by
Jiacheng Zhang, Yang Liu, Huanbo Luan, Jingfang Xu, Maosong Sun
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as a article
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2018
Abstract
Although neural machine translation has made significant progress recently,
how to integrate multiple overlapping, arbitrary prior knowledge sources
remains a challenge. In this work, we propose to use posterior regularization
to provide a general framework for integrating prior knowledge into neural
machine translation. We represent prior knowledge sources as features in a
log-linear model, which guides the learning process of the neural translation
model. Experiments on Chinese-English translation show that our approach leads
to significant improvements.
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1811.01100v1
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