Language Acquisition and Probabilistic Models: keeping it simple

[Thierry Poibeau]

Chers collègues, 

Je vous rappelle le séminaire suivant, demain matin salle Cartan (au 45 rue d’Ulm). 

Venez nombreux !

Thierry


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Aline Villavicencio (Universidade Federal Rio Grande do Sul, Brésil)

Language Acquisition and Probabilistic Models: keeping it simple
Joint work with Bob Berwick (MIT)

Abstract: Hierarchical Bayesian Models (HBMs) have been used with some success to capture empirically observed patterns of under- and overgeneralization in child language acquisition. However, as is well known, HBMs are ``ideal'' learning systems, assuming access to unlimited computational resources that may not be available to child language learners. Consequently, it remains crucial to carefully assess the use of HBMs along with alternative, possibly simpler, candidate models. In this talk I describe an evaluation for a language acquisition domain where explicit HBMs have been proposed: the acquisition of English dative constructions. In particular, I present a detailed, empirically-grounded model-selection comparison of HBMs vs. a simpler alternative based on clustering along with maximum likelihood estimation, the linear competition learning (LCL). Results obtained demonstrate that LCL can match HBM model performance without incurring on the high computational costs associated with HBMs.

Mercredi 7 mars
10h30 - 12h30, ENS 45 rue d’Ulm salle Cartan

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