Complexity of frequency fluctuations and the interpretive style in the bass viola da gamba

TL;DR

This study models the frequency fluctuations in bass viola da gamba music as complex networks, revealing statistical regularities and influential sound groups that relate to interpretive styles and musical events.

Contribution

It introduces a novel interdisciplinary approach combining spectral analysis and complex network theory to analyze musical frequency fluctuations.

Findings

Identified statistical distributions describing frequency fluctuations.

Confirmed influential sound groups via centrality measures.

Linked large-scale regularities to musical interpretive styles.

Abstract

Audio signals in a set of musical pieces are modeled as a complex network for studying the relationship between the complexity of frequency fluctuations and the interpretive style of the bass viola da gamba. Based on interdisciplinary scientific and music approaches, we compute the spectral decomposition and translated its frequency components to a network of sounds. We applied a best fit analysis for identifying the statistical distributions that describe more precisely the behavior of such frequencies and computed the centrality measures and identify cliques for characterizing such a network. Findings suggested statistical regularities in the type of statistical distribution that best describes frequency fluctuations. The centrality measure confirmed the most influential and stable group of sounds in a piece of music, meanwhile the identification of the largest clique indicated functional groups of sounds that interact closely for identifying the emergence of complex frequency fluctuations. Therefore, by modeling the sound as a complex network, we can clearly associate the presence of large-scale statistical regularities with the presence of similar frequency fluctuations related to different musical events played by a same musician.