Guitar Solos as Networks
This addresses the problem of analyzing and processing music for applications in multimedia, though it is incremental as it applies existing network theory to a new domain.
The paper models melodies as directed networks where notes are nodes connected by sequence, applying complex network theory to extract metrics from guitar solos. The results suggest this model can impact multimedia applications like music classification, identification, and automatic generation.
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.