Attractors of variation in Hungarian inflectional morphology

Abstract

Abstract We use algorithmic learning and statistical methods over a form frequency list (compiled from the Hungarian web corpus) to investigate variation in Hungarian verbal inflection. Our aims are twofold: (i) to give an adequate description of this variation, which has not been described in detail in the literature and (ii) to explore the range and depth of lexical attractors that potentially shape this variation. These attractors range from closely related ones, such as the shape of the word form or the behaviour of the verb’s paradigm, to broad ones, such as the behaviour of similar verbs or the phonotactics of related verb forms. We find that verbal variation is predominantly determined by similarity to related verb forms rather than by word shape or by word frequency. What is more, the effect of similarity is better approximated using inflected forms as opposed to base forms as points of comparison. This, in turn, supports a rich memory model of morphology and the mental lexicon.