Title: Constraining the Phrase-Based, Joint Probability Statistical Translation Model.
Abstract: The Joint Probability Model proposed by Marcu and Wong (2002) provides a probabilistic framework for modeling phrase-based statistical machine transla- tion (SMT). The model’s usefulness is, however, limited by the computational complexity of estimating parameters at the phrase level. We present a method of constraining the search space of the Joint Probability Model based on statistically and linguistically motivated word align- ments. This method reduces the complexity and size of the Joint Model and allows it to display performance superior to the standard phrase-based models for small amounts of training material.
Publication Year: 2006
Publication Date: 2006-08-08
Language: en
Type: article
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Cited By Count: 9
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