Goldwater, Sharon

Griffiths, Thomas

Johnson, Mark

English

Johnson, Mark E

Griffiths, Thomas L

Macquarie University ResearchOnline

Bayesian Inference for PCFGs via Markov Chain Monte Carlo

This paper presents two Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference of probabilistic context free grammars (PCFGs) from terminal strings, providing an alternative to maximum-likelihood estimation using Inside-Outside algorithm. We illustrate these methods by estimating a sparse grammar describing the morphology of the Bantu language Sesotho, demonstrating that with suitable priors Bayesian techniques can infer linguistic structure in situations where maximum likelihood methods such as Inside-Outside algorithm only produce a trivial grammar

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Bayesian Inference for PCFGs via Markov Chain Monte Carlo

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