This paper explores the learning of phonotactics in neural networks. Experiments are conducted on the complete set of over 5,000 Dutch monosyllables extracted from CELEX, and the results are shown to be accurate within 5% error. Extensive comparisons to human phonotactic learning conclude the paper. We focus on whether phonotactics can be effectively learned and how the learning which is induced compares to human behavior.
