Clustering and Classification of Music by Interval Categories

Abstract

Abstract. In this paper, we present a novel approach to clustering and classification of music. The approach is based on the concept of interval categories, which is a theoretical, but perceptually motivated construct that groups sets of pitch events into six different categories each of which has its own musical character. A piece of music can be represented by six percentages that express the occurrences of each category in the piece. This piece of music can, in this way, be represented as one point in a six dimensional space. We choose the three most significant dimensions to visualize music from different composers and genres. We will see that, using this approach, automatic classification between tonal and atonal music is possible. Furthermore, we will present a successful visual clustering of 1) the three periods of Beethoven, 2) the genres Rock and Jazz, and 3) several composers through various musical time periods.

Wavescapes: A visual hierarchical analysis of tonality using the discrete Fourier transform

“…In sum, the interpretations of the six coefficients resonate well with music-theoretical descriptions (Amiot, 2016; Lewin, 2001; Yust, 2019b) and empirical findings (Honingh & Bod, 2010, 2011), as the chromatic circle and the circle of fifths are fundamental structures for Western classical music and jazz (Aldwell et al, 2010; Rohrmeier, 2020). Furthermore, the highly dissonant harmonies of post- and atonal music (Straus, 2005) maximize magnitudes for the first two coefficients.…”