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%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