AUDIO DESCRIPTIVE ANALYSIS OF SINGER AND MUSICAL INSTRUMENT IDENTIFICATION IN NORTH INDIAN CLASSICAL MUSIC

Abstract

Music information retrieval (MIR) has reached to a reasonably stable state after advancement in the Low Level audio Descriptors (LLDs) and feature extraction techniques. The analysis of sound has now become simple by the continuous efforts and research of MIR community in the field of signal processing from last two decades. In north Indian classical music, a singer is accompanied by some instruments such as harmonium, violin or flute. These instruments are tuned in the same musical scale (pitch range) in which the singer is signing. Separate researches have been made in recent past to identify a musical instrument and a singer. In this paper, we have analyzed the low level audio descriptors, for singing voice and musical instrument sound together, that appears to human ear as similar with respect to ‘timbre’, to see if we could treat them same and use identification/ classification routines to classify them into their classes. We have used Hybrid Selection algorithm from wrapper technique(the one that uses classifier also in feature selection process) to identify and extract the features and K-Means and K nearest neighbor classifiers to classify and cross verify the accuracy of classification. The accuracy of classification achieved was 91.1% which clearly proves that musical instruments and singing voice that sounds similar in timbral aspect can be grouped together and classification is possible with mixed database of instruments and singing voices.