Word Learning Using a Self-Organizing Map

SOMs have been successfully applied in various fields. In this paper, we proposed an expanded SOM model for word learning which is a classic problem in cognitive science. In spite of simple computation of this model, the simulation results are consistent with the conclusion of the newest Bayesian model in the same learning cases. It implies that this model has the ability like human to properly response to different number and span of samples.