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Artificial language learning research has shown that, under some conditions, adult speakers tend to probability-match to inconsistent variation in their input, while in others, they regularize by reducing that variation. We demonstrate that this framework can characterize speaker behavior in a natural-language morphological inflection task: 
the lexicon can be used to estimate variation in speaker productions. In the task of German plural inflection, we find that speakers probability-match a lexical distribution conditioned on phonology, and largely disregard an alternative possible strategy of conditional regularization based on grammatical gender.

CogSci 2022

Regularization or lexical probability-matching? How German speakers generalize plural morphology

technical paper

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Regularization or lexical probability-matching? How German speakers generalize plural morphology

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