Obtaining a minimal set of rewrite rules
نویسنده
چکیده
In this paper we describe a new approach to rewrite rule extraction and analysis, using Minimal Representation Graphs. This approach provides a mechanism for obtaining the smallest possible rule set – within a context-dependent rewrite rule formalism – that describes a set of discrete training data completely, as an indirect approach to obtaining optimal accuracy on an unseen test set. We demonstrate the application of this technique for a pronunciation prediction task.
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تاریخ انتشار 2005