Abstract
This dissertation proposes Emergent Feature Theory, a unified account of what were previously considered to be natural and unnatural classes. These classes are accounted for on the basis of phonetically-based generalization, sound change, and other factors, obviating the need to assume innate distinctive features. Evidence for the proposal comes from the first large-scale survey of natural classes. Based on data from 561 languages, the survey reveals that unnatural classes are widespread: among 6077 unique classes of sounds which are targets or triggers of phonological processes, analyzed in three popular feature theories (Preliminaries, Jakobson, Fant, and Halle 1954; SPE, Chomsky and Halle 1968; and Unified Feature Theory, Clements and Hume 1995), no single theory is able to characterize more than 71% of the classes, and over 24% are not characterizable in any of the theories. While other theories are able to account for specific subsets of these classes, none is able to predict the wide range of classes which actually occur and recur. It is shown that there is no objective way to partition classes into natural and idiosyncratic categories. Even without these findings, there are many reasons to be suspicious of the idea that distinctive features are innate. Humans have been evolving (separate from other primates) for a relatively short time. For all distinctive features, including the uncommon ones, to have emerged in the human genome, humans must have been exposed to contrasts motivating all of them at some time before the life of a common ancestor of all modern humans who would have all these features (all humans). This includes the distinctive features for sign languages, which appear to use entirely different phonological features and feature organization, even though deafness is generally not hereditary. All of this evidence, along with the survey results, point to the conclusion that the distinctive features used in language are learned rather than innate.
