"All mimsy were the borogoves” – A discriminative learning model of morphological knowledge in pseudo-word inflection

Grammatical knowledge of native speakers has often been investigated in so-called wug tests, in which participants have to inflect pseudo-word forms (wugs). Typically it has been argued that in inflecting these pseudo-words, speakers apply their knowledge of word formation processes. However, it remains unclear what exactly this knowledge is and how it is learned.According to one theory, the knowledge is best characterized as abstractions and rules that specify how units can be combined. Another theory maintains that it is best characterized by analogy. In both cases the knowledge is learned by association based on positive evidence alone.In this paper, we model the classification of pseudo-words to Maltese plural classes on the basis of phonetic input using a shallow neural network trained with an error-driven learning algorithm. We demonstrate that the classification patterns mirror those of Maltese native speakers in a wug test. Our results indicate that speakers rely on gradient knowledge of a relation between the phonetics of whole words and plural classes, which is learned in an error-driven way.