Semantic Parsing with Bayesian Tree Transducers

Many semantic parsing models use tree transformations to map between natural language and meaning representation. However, while tree transformations are central to several state-of-the-art approaches, little use has been made of the rich literature on tree automata. This paper makes the connection concrete with a tree transducer based semantic parsing model and suggests that other models can be interpreted in a similar framework, increasing the generality of their contributions. In particular, this paper further introduces a variational Bayesian inference algorithm that is applicable to a wide class of tree transducers, producing state-of-the-art semantic parsing results while remaining applicable to any domain employing probabilistic tree transducers.

• Type: Journal
• Year: 2012
• Where: ACL
• Authors: Bevan K. Jones, Mark Johnson, Sharon Goldwater
• Keywords: ACL 2012, Computational Linguistics, Inference Algorithm, Tree Transducers, Tree Transformations