Music instrument recognition: From isolated notes to solo phrases

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 4, Issue , 2004, Pages

  Krishna, A G ^a   Sreenivas, T V ^a  

^a INDIAN INSTITUTE OF SCIENCE   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; AUTOMATION; DIGITAL FILTERS; FREQUENCIES; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; MUSICAL INSTRUMENTS; PATTERN RECOGNITION; POLYNOMIALS; SPEECH PROCESSING;

AUDIO PROCESSING; AUTOMATIC SPEECH RECOGNITION (ASR); MUSIC INSTRUMENT RECOGNITION; SPEAKER IDENTIFICATION (SID);

COMPUTER MUSIC;

EID: 4544247190     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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3. J. Marques and P. Moreno, A study of musical instrument classification using gaussian mixture models and support vector machines, Cambridge Research Labs Technical Report Series CRL/4, 1999
4. A. Eronen and A. Klapuri, Music instrument recognition using cepstral coefficients and temporal features, Proc. of ICASSP, pp. 753-756, 2000.
5. A. Eronen, Comparison of features for musical instrument recognition, Workshop on Signal Processing for Audio and Acoustics(WASPAA), pp. 19-22, 2001.
6. G. Agostini, M. Longari and E. Pollastri, Music instrument timbres classification with spectral features, Proc. of ICME, pp. 97-102, 2001.
7. T. Kitahara, M. Goto and H. G. Okuno, Music instrument identification based on FO dependent multivariate normal distribution, Proc. of ICASSP, pp. 421-424, 2003.
8. K. K. Paliwal and B. S. Atal, Efficient vector quantization of LPC parameters at 24 bits/frame, IEEE Transactions on Speech and Audio Processing, Vol. 1, pp. 3-14, Jan., 1993.