Retentional Syntagmatic Network, and its Use in Motivic Analysis of Maqam Improvisation

In this paper is defined a concept of Retentional Syntagmatic Network (RSN), which models the connectivity between temporally closed notes. The RSN formalizes the Schenkerian notion of pitch prolongation as a concept of syntagmatic retention, whose characteristics are dependent on the underlying modal context. This framework enables to formalize the syntagmatic role of ornamentation, and allows an automation of motivic analysis that takes into account melodic transformations. The model is applied to the analysis of a maqam improvisation. The RSN is also proposed as a way to surpass strict hierarchical segmentation models, which in our view cannot sufficiently describe the richness of musical structure. Instead of separability, we propose to focus instead on the connectivity between notes, modeled with the help of RSNs

Motivic Pattern Mining

This paper presents a concise overview of a research project dedicated to Motivic Pattern Mining, i.e., the automatic discovery of motives within pieces of music through a search for repetitions in score representations