Speeding Up Syntactic Learning using Contextual Information

Abstract

It has been shown in (Angluin and Becerra-Bonache, 2010, 2011) that interactions between a learner and a teacher can help language learning. In this paper, we make use of additional contextual information in a pairwise-based generative approach aiming at learning (situation,sentence)-pair-hidden markov models. We show that this allows a significant speed-up of the convergence of the syntactic learning. We apply our model on a toy natural language task in Spanish dealing with geometric objects.

Publication
In International Conference on Grammatical Inference (ICGI), 2012