Raga identification from Hindustani classical music signal using compositional properties

Classification of music signal is a fundamental step for organized archival of music collection and fast retrieval thereafter. For Indian classical music, raga is the basic melodic framework. Manual identification of raga demands high expertise which is not available easily. Thus an automated system for raga identification is of great importance. In this work, we have studied the basic properties of the ragas in North Indian (Hindusthani) classical music and designed the features to capture the same. Pitch based Swara (note) profile is formed. Occurrence and energy distribution of notes generated from the profile are used as features. Note sequence plays an important role in the raga composition. Proposed note co-occurrence matrix summarizes this aspect. An audio clip is represented by these features which have strong correlation with the properties of raga. Support vector machine is used for classification. Experiment is done with a diversified dataset. Performance of the proposed work is compared with two other systems. It is observed that proposed methodology performs better.