Unsupervised Grammar Learning with a Curriculum
Kewei Tu and Vasant Honavar
We examine the utility of a curriculum (a means of presenting training samples in a meaningful order) in unsupervised learning of probabilistic grammars. We introduce a hypothetical explanation of the advantages of using a curriculum in grammar learning, which offers some useful insights into the design of curricula as well as learning algorithms. We present results of experiments with (a) carefully crafted synthetic data that provide support for our hypothesis and (b) natural language corpus that demonstrate the utility of curricula in unsupervised learning of probabilistic grammars.