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Abstract:
Carnatic Music is a South Indian art and devotional musical practice in which melodic patterns (motifs and phrases), known as sañcaras ¯ , 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 variablelength, 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 ¯
in Carnatic Music. Experimental results show that the proposed method is able to identify 54% of all sañcaras ¯ annotated by a professional Carnatic vocalist. Code to reproduce and interact with these results is available online
