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HarmTrace: Improving Harmonic Similarity Estimation Using Functional Harmony Analysis

Harmony theory has been essential in composing, analysing, and performing music for centuries. Since Western tonal harmony exhibits a considerable amount of structure and regularity, it lends itself to formalisation. In this paper we present HARMTRACE, a system that, given a sequence of symbolic chord labels, automatically derives the harmonic function of a chord in its tonal context. Among other applications, these functional annotations can be used to improve the estimation of harmonic similarity in a local alignment of two annotated chord sequences. We evaluate HARMTRACE and three other harmonic similarity measures on a corpus of 5,028 chord sequences that contains harmonically related pieces. The results show that HARMTRACE outperforms all three other similarity measures, and that information about the harmonic function of a chord improves the estimation of harmonic similarity between two chord sequences.