A model of large-scale thematic structure

Abstract

The coherent organisation of thematic material into large-scale structures within a composition is an important concept in both traditional and cognitive theories of music. However, empirical evidence supporting their perception is scarce. Providing a more nuanced approach, this paper introduces a computational model of hypothesised cognitive mechanisms underlying perception of large-scale thematic structure. Repetition detection based on statistical learning forms the model's foundation, hypothesising that predictability arising from repetition creates perceived thematic coherence. Measures are produced that characterise structural properties of a corpus of 623 monophonic compositions. Exploratory analysis reveals the extent to which these measures vary systematically and independently.