A MDL-based Model of Gender Knowledge AcquisitionHarmonyMarchalauthorBenoitLemaireauthorMaryseBiancoauthorPhilippeDessusauthorThis 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.Applied Cognitive PsychologyComputational Linguistics2008Association for Computational LinguisticsConference Paper