PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Speeding Up Syntactic Learning Using Contextual Information
Leonor Becerra, Elisa Fromont, Amaury Habrard, Michaël Perrot and Marc Sebban
JMLR Workshop and Conference Proceedings Volume 21, pp. 49-53, 2012.

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.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:9586
Deposited By:Leonor Becerra
Deposited On:17 October 2012