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Inference for PCFGs and Adaptor Grammars

This video was recorded at NIPS Workshops, Whistler 2009. 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.

Keywords:: videolectures, ocwc, oec

Disciplines:

Science and Technology / Computer Science / Programming & Programming Languages

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Material Type:: Presentation
Date Added to MERLOT:: February 10, 2015
Date Modified in MERLOT:: February 10, 2015
Author:: Mark Johnson, Brown Laboratory for Linguistic Information Processing, Brown University
Submitter:: The Open Education Consortium
Primary Audience:: College General Ed, College Lower Division, College Upper Division
Technical Format:: Video

Mobile Compatibility:: Not specified at this time
Language:: English
Cost Involved:: No
Source Code Available:: No
Creative Commons:: This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States