Memory-based Models of Melodic Analysis: Challenging the Gestalt Principles

We argue for a memory-based approach to music analysis which works with concrete musical experiences rather than with abstract rules or principles. New pieces of music are analyzed by combining fragments from structures of previously encountered pieces. The occurrence-frequencies of the fragments are used to determine the preferred analysis of a piece. We test some instances of this approach against a set of 1,000 manually annotated folksongs from the Essen Folk-song Collection, yielding up to 85.9% phrase accuracy. A qualitative analysis of our results indicates that there are grouping phenomena that challenge the commonly accepted Gestalt principles of proximity, similarity and parallelism. These grouping phenomena can neither be explained by other musical factors, such as meter and harmony. We argue that music perception may be much more memory-based than previously assumed.