Inference for PCFGs and Adaptor Grammars
published: Jan. 19, 2010, recorded: December 2009, views: 4909
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
This talk describes the procedures we've developed for adaptor grammar inference. Adaptor grammars are a non-parametric extension to PCFGs that can be used to describe a variety of phonological and morphological language learning tasks. We start by reviewing an MCMC sampler for Probabilistic Context-Free Grammars that serves as the basis for adaptor grammar inference, and then explain how samples from a PCFG whose rules depend on the other sampled trees can be used as a proposal distribution in an MCMC procedure for estimating adaptor grammars. Finally we describe several optimizations that dramatically speed inference of complex adaptor grammars.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !