Instrumental/song classification of music signal using RANSAC

In a music retrieval system, classification of music data serves as the fundamental step for organizing the database to support faster access of desired data. In this context, it is very important to classify the music signal into the two sub-categories namely instrumental and song. A robust system for such classification will enable to go for further classification based on instrument type or music genre. In this work, we have presented a simple but novel scheme using Mel Frequency Cepstral Co-efficients (MFCC) as the signal descriptors. A classifier based on Random Sample and Consensus (RANSAC), capable of handling wide variety of data has been used. Experimental result indicates that proposed scheme works fine for a wide variety of music signals.