What a Perceptron Reveals about Metrical Phonology

Metrical phonology is a relatively successful theory that attempts to explain stress systems in language. This paper discusses a perceptron model of stress, pointing out interesting parallels between certain aspects of the model and the constructs and predictions of metrical theory. The distribution of learning times obtained from perceptron experiments corresponds with theoretical predictions of “markedness.” In addition, the weight patterns developed by perceptron learning bear a suggestive relationship to features of the linguistic analysis, particularly with regard to iteration and metrical feet. Our results suggest that simple statistical learning techniques have the potential to complement, and provide computational validation for, abstract theoretical investigations of linguistic domains.