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The state-of-the-art statistical machine translation models are trained with the parallel corpora. However, the traditional SMT loses its power when it comes to language pairs with few bilingual resources. This paper proposes a novel method that treats the phrase extraction as a classification task. We first automatically generate the training and testing phrase pairs for the classifier. Then, we...
The training procedure is very important in statistical machine translation (SMT). It has a great influence on the final performance of a translation system. The widely used method in SMT is the minimum error rate training (MERT). It is effective to estimate the feature function weights. However, MERT does not use regularization and has been observed to over-fit. In this paper, we describe a method...
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