Paper: A Gibbs Sampler for Phrasal Synchronous Grammar Induction

ACL ID P09-1088
Title A Gibbs Sampler for Phrasal Synchronous Grammar Induction
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

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 sam- pler 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 transla- tion corpora than previous approaches.