Abstract

This paper describes how to cluster together the phrases of a phrase-based statistical machine translation (SMT) system, using information in the phrase table itself. The clustering is symmetric and recursive: it is applied both to sourcelanguage and target-language phrases, and the clustering in one language helps determine the clustering in the other. The phrase clusters have many possible uses. This paper looks at one of these uses: smoothing the conditional translation model (TM) probabilities employed by the SMT system. We incorporated

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