Guitar Solos as Networks

TL;DR

This paper models guitar solos as directed networks using complex network theory, enabling analysis of musical structure and potential applications in music classification, identification, and generation.

Contribution

It introduces a novel network-based framework for analyzing melodies, specifically guitar solos, using complex network metrics.

Findings

Network metrics characterize different guitar solos.

Model can improve music classification and identification.

Potential for automatic music generation applications.

Abstract

This paper presents an approach to model melodies (and music pieces in general) as networks. Notes of a melody can be seen as nodes of a network that are connected whenever these are played in sequence. This creates a directed graph. By using complex network theory, it is possible to extract some main metrics, typical of networks, that characterize the piece. Using this framework, we provide an analysis on a set of guitar solos performed by main musicians. The results of this study indicate that this model can have an impact on multimedia applications such as music classification, identification, and automatic music generation.