PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Gibbs Sampler for Phrasal Synchronous Grammar Induction
Phil Blunsom, Trevor Cohn, Miles Osborne and Chris Dyer
In: ACL 2009, 2-7 August, Singapore.

Abstract

We present a phrasal synchronous gram- mar model of translational equivalence. Unlike previous approaches, we do not resort to heuristics or constraints from a word-alignment model, but instead directly induce a synchronous grammar from parallel sentence-aligned corpora. We use a hierarchical Bayesian prior to bias towards compact grammars with small translation units. Inference is per- formed using a novel Gibbs sampler over synchronous derivations. This sampler side-steps the intractability issues of previous models which required inference over derivation forests. Instead each sam- pling iteration is highly efficient, allowing the model to be applied to larger translation corpora than previous approaches.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Natural Language Processing
ID Code:6747
Deposited By:Phil Blunsom
Deposited On:08 March 2010