Distributional learning of lexical tone and musical pitch by naÀ ve and experienced adult learners

Abstract

Language and music are two human universals that share many commonalities, including processes of statistical and distributional learning in acquiring knowledge of those domains. This thesis is concerned with the role of distributional learning in the acquisition of pitch-based building blocks of speech and music. In a series of five studies, questions of theoretical and empirical interest will be examined, whether: (i) distributional learning can be used to acquire lexical tone and musical pitch; (ii) domain-general or domain-specific pitch experience facilitates distributional learning of pitch; and (iii) distributional learning plays a role in cross-domain transfer. The results of all five studies suggest that distributional learning can be used to acquire the foundations of speech and music; using distributional learning, adult learners either shift existing category boundaries to which the perceptual items assimilate or form new categories if the perceptual items are not assimilated to any native (linguistic or musical) categories. While distributional learning appears to be sensitive to top-down interferences and is modulated by domain-specific experience, it is nonetheless a powerful learning mechanism that is generalisable across domain. This thesis thus advances our understanding of speech and music by providing evidence for the commonality between the two in terms of a common learning mechanism and shared pitch processing, both of which are compatible with accounts of a common origin for language and music.

Date of Award	2016
Original language	English