DocumentCode :
117586
Title :
Musical instrument classification using higher order spectra
Author :
Bhalke, D.G. ; Rao, C. B. Rama ; Bormane, Dattatraya S.
Author_Institution :
Dept. of ECE, Nat. Inst. of Technol., Warangal, India
fYear :
2014
fDate :
20-21 Feb. 2014
Firstpage :
40
Lastpage :
45
Abstract :
This paper presents classification and recognition of monophonic isolated musical instrument sounds using higher order spectra such as Bispectrum and Trispectrum. Experimental results on a widely used dataset shows that higher order spectra based features improve the recognition accuracy, when combined with conventional features such as Mel Frequency Cepstral Coefficient (MFCC), Cepstral, Spectral and Temporal features. Nineteen western musical instruments covering four families with full pitch range have been used for experimentation.
Keywords :
music; pattern classification; MFCC; Mel frequency cepstral coefficient; bispectrum; cepstral features; full pitch range; higher order spectra; monophonic isolated musical instrument sounds classification; monophonic isolated musical instrument sounds recognition; recognition accuracy; spectral features; temporal features; trispectrum; western musical instruments; Accuracy; Feature extraction; Instruments; Mel frequency cepstral coefficient; Music; Neural networks; Signal processing; Bispectrum; MFCC; Spectral; Temporal; Trispectrum;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Integrated Networks (SPIN), 2014 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-2865-1
Type :
conf
DOI :
10.1109/SPIN.2014.6776918
Filename :
6776918
Link To Document :
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