On the role of locality in learning stress patterns

This paper presents a previously unnoticed universal property of stress patterns in the world's languages: they are, for small neighbourhoods, neighbourhood-distinct. Neighbourhood-distinctness is a locality condition defined in automata-theoretic terms. This universal is established by examining stress patterns contained in two typological studies. Strikingly, many logically possible - but unattested - patterns do not have this property. Not only does neighbourhood-distinctness unite the attested patterns in a non-trivial way, it also naturally provides an inductive principle allowing learners to generalise from limited data. A learning algorithm is presented which generalises by failing to distinguish same-neighbourhood environments perceived in the learner's linguistic input - hence learning neighbourhood-distinct patterns - as well as almost every stress pattern in the typology. In this way, this work lends support to the idea that properties of the learner can explain certain properties of the attested typology, an idea not straightforwardly available in optimality-theoretic and Principle and Parameter frameworks.