Graph Representation of RaagBase: A Unique Dataset for Hindustani Music
2026-07-11 • Sound
Sound
AI summaryⓘ
The authors created RaagBase, a new dataset that uses note sequences from Pt. Bhatkhande's compositions to study raags in Hindustani music. They represent each composition as a node in a graph and connect nodes based on how similar their note frequencies are. Using graph clustering methods, they group compositions into clusters that match known raag categories well. This work helps in organizing and understanding raags without needing labeled audio data, and the dataset is made publicly available.
Raag classificationHindustani Musicnote sequencesgraph clusteringmusic information retrievalPt. Bhatkhandenote frequency distributionmusic datasettemporal structure
Authors
Chandan Misra, Swarup Chattopadhyay
Abstract
Raag classification is a fundamental MIR task for Hindustani Music, with applications in recommendation, education, archiving, and intelligent search. However, raag clustering remains underexplored, as most existing approaches rely on annotated audio or labeled datasets. While annotated melodic phrases capture characteristic patterns, complete note sequences preserve temporal structure and contextual dependencies, making them more suitable for data-driven modeling. In this work, we introduce RaagBase, a notation-based text dataset consisting of note sequences from compositions by Pt. Bhatkhande. Furthermore we propose a novel graph-based representation of raag structures by modeling the dominance and absence of notes in compositions. Each composition is represented as a node, and the edges between two compositions corresponds the similarities between them based on the note frequency distribution. Further, we apply established graph clustering techniques to identify groups of similar raag compositions. Experimental results demonstrate highly coherent clusters with strong agreement to ground-truth raag labels, thereby validating both the dataset and the proposed representation. The dataset is publicly available at https://anonymous.4open.science/r/RaagBase-5427.