  Ragas form the foundation for Indian Classical Music. The task of Raga
Recognition has gained traction in the Music Information Retrieval community in
the recent past, which can be attributed to the nuances of Indian Classical
Music that have resulted in a plethora of research problems in Computing. In
this work, we used two different digital audio signal processing techniques to
preprocess audio samples of Carnatic classical ragas that were then processed
by various Deep Learning models. Their results were compared in order to infer
which DASP technique is better suited to the task of raga recognition. We
obtained state of the art results, with our best model reaching a testing
accuracy of 98.1%. We also compared each model ability to distinguish between
similar ragas.
