Improving A Lexicalized Hierarchical Reordering Model Using Maximum Entropy
نویسندگان
چکیده
In this paper, we present a reordering model based on Maximum Entropy. This model is extended from a hierarchical reordering model with PBSMT (Galley and Manning, 2008), which integrates syntactic information directly in decoder as features of MaxEnt model. The advantages of this model are (1) maintaining the strength of phrase based approach with a hierarchical reordering model, (2) many kinds of linguistic information integrated in PBSMT as arbitrary features of MaxEntropy model. The experiment results with English-Vietnamese pair showed that our approach achieves improvements over the system which use a lexical hierarchical reordering model (Galley and Manning, 2008).
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تاریخ انتشار 2009