Inside-Outside Algorithm for Macro Grammars.
The 15th International Conference on Grammatical Inference,
Proceedings of Machine Learning Research Vol.153, pp.32-46
(2021), [peer-reviewed]
Event Date:
August 23-27, 2021
@ virtual
Abstract / 概要
We propose an inside-outside algorithm for stochastic macro grammars. Our approach is based on types, which has been inspired by type-based approaches to reasoning about functional programs and higher-order grammars. By considering type derivations instead of ordinary word derivation sequences, we can naturally extend the standard inside-outside algorithm for stochastic context-free grammars to obtain the algorithm for stochastic macro grammars. We have implemented the algorithm and confirmed its effectiveness through an application to the learning of macro grammars.