Radical substance-free phonology and feature learning

Abstract

Abstract This article argues that phonological features have no substantive properties, instead, segments are assigned features by learning strategies set to the task of devising a computational system for a phonology that is consistent with the requirements of UG. I address two problems for such a substance-free model. The first is the Card-Grammar problem, which has been suggested to argue for universal substantive features, on the premise that, otherwise, language data cannot be stored in a fashion necessary to correct learning errors. The Card Grammar problem disappears, in a suitably modular theory of mind with learned interfaces, where the mind still can retain information not parsed in a particular grammar. The second problem is the need for a demonstration, not just an assertion, that a reasonable theory of grammar and learning which has no access to phonetic substance can yield a coherent system of feature assignments. This is accomplished by modeling the learning of features necessary for the phonology of Kerewe.