Raga Recognition in Indian Carnatic Music Using Convolutional Neural Networks

Abstract

A vital aspect of Indian Classical music (ICM) is raga, which serves as a melodic framework for compositions and improvisations for both traditions of classical music. In this work, we propose a CNN-based sliding window analysis on mel-spectrogram and modgdgram for raga recognition in Carnatic music. The impor- tant contribution of the work is that the pro- posed method neither requires pitch extraction nor metadata for the estimation of raga. CNN learns the representation of raga from the pat- terns in the melspectrogram/ modgdgram dur- ing training through a sliding-window analysis. We train and test the network on sliced-mel- spectrogram/modgdgram of the original audio while the nal inference is performed on the au- dio as a whole. The performance is evaluated on 15 ragas from the CompMusic dataset. Multi- stream fusion has also been implemented to identify the potential of two feature representations. Multi-stream architecture shows promise in the proposed scheme for raga recognition.