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In this study, we employ a computational model that formalizes music-theoretic conceptualizations of tonal space, and use it to infer the most likely interval distributions for pieces in a large corpus of music, represented as so-called ‘bags of tonal pitch classes’.

We present a dataset of 264 annotated piano pieces of nine composers, composed in the long 19th century.

In this study, we determine the fundamental role of the line of fifths for the organization of tonal material by applying dimensionality reduction to a large historical corpus of pitch-class counts (ca. 1360–1940). We observe a historically growing trend in the exploitation of the fifths range, i.e. the size of segments that pitch-class distributions cover on the line of fifths. Moreover, we introduce the novel concept of pitch-class (co-)evolution.

We introduce wavescapes, a novel visualization method for tonal hierarchies that combines the visual representation of keyscapes with music analysis based on the discrete Fourier transformation (DFT) and illustrate it by analyzing compositions by Josquin, Bach, Liszt, Chopin, Scriabin, Webern, Coltrane, and Ligeti.

In this study, we use the Latent Dirichlet Allocation (LDA) topic model to discover tonal structures in a corpus of more than 2000 musical pieces from large historical range (ca. 600 years). and that the inferred topics have music-theoretically meaningful interpretations.