Abstract
Musical instrument recognition becomes an important aspect of music information retrieval which can be used by Musician and lay man to understand it. In this paper, Dynamic time warping techniques is utilized to recognize Indian musical instruments using 39 MFCC features. Six Indian musical instruments from different families are considered in this work. A large audio database are collected and recorded in our Lab at 44.1 KHz sampling frequency. Training and test templates are generated using 39 MFCC features. Sixty three different features of instrument are studied including temporal, spectral and cepstral features. In this paper we have implemented MFCC algorithm, silence part removal using Energy and Zero crossing rate and DTW algorithm. For classification task, experimental results are provided using MFCC, delta MFCC, delta delta MFCC and DTW. It is proposed that higher recognition rates can be achieved using MFCC features with DTW which is useful for different time varying musical notes‥
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