In search of Sañcāras: tradition-informed repeated melodic pattern recognition in carnatic music

Abstract

Carnatic Music is a South Indian art and devotional musical practice in which melodic patterns (motifs and phrases), known as sañcaras Å , play a crucial structural and expressive role. We demonstrate how the combination of transposition invariant features learnt by a Complex Autoencoder (CAE) and predominant pitch tracks extracted using a Frequency-Temporal Attention Network (FTANet) can be used to annotate and group regions of variable-length, repeated, melodic patterns in audio recordings of multiple Carnatic Music performances. These models are trained on novel, expert-curated datasets of hundreds of Carnatic audio recordings and the extraction process tailored to account for the unique characteristics of sañcaras Å in Carnatic Music. Experimental results show that the proposed method is able to identify 54% of all sañcaras Å annotated by a professional Carnatic vocalist. Code to reproduce and interact with these results is available online.