Raga Identification Using MFCC and Chroma features

Abstract

Ragas are the heart of Indian classical music. Raga is one of the basic concepts in Indian music. Raga plays an important role in Indian classical music. It is a collection of swaras comprising of many features and is explained as melodic concept which is led to blossom by the musical artist. We have performed this approach on 3 ragas Darbari, Khamaj, and Malhar. In this work, we propose a methodology to identify the ragas of an Indian music signal. This has several interesting applications in digital music indexing, recommendation and retrieval. In this work, we attempt the raga classification problem in a nonlinear SVM (support vector machine) framework using a combination of two relevant features that represent the similarities of a music signal using two different features MFCC (Mel Frequency Cepstral Coefficient) and Chromagram. We assesses the proposed method on our own raga dataset achieve an improvement of 96.79% in accuracy by combining the information from two features relevant to Indian music.