%A Harmony Marchal
%A Benoit Lemaire
%A Maryse Bianco
%A Philippe Dessus
%T A MDL-based Model of Gender Knowledge Acquisition
%X This paper presents an iterative model of
knowledge acquisition of gender information
associated with word endings in
French. Gender knowledge is represented
as a set of rules containing exceptions.
Our model takes noun-gender pairs as input
and constantly maintains a list of
rules and exceptions which is both coherent
with the input data and minimal with
respect to a minimum description length
criterion. This model was compared to
human data at various ages and showed a
good fit. We also compared the kind of
rules discovered by the model with rules
usually extracted by linguists and found
interesting discrepancies.
%K gender assignment,computational model,minimum description length
%E Alex Clark
%E Kristina Toutanova
%D 2008
%I Association for Computational Linguistics
%L cogprints6177

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