Efficient Pitch Detection Techniques for Interactive Music

International Computer Music Conference, ICMC Proceedings

Volumn , Issue , 2001, Pages

  de la Cuadra, Patricio ^a   Master, Aaron ^a   Sapp, Craig ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER MUSIC; MUSIC;

CEPSTRUM; INTERACTIVE COMPUTER MUSIC; INTERACTIVE MUSIC; MUSIC PERFORMANCE; PITCH DETECTION; PITCH DETECTION ALGORITHM; PITCH-TRACKING; PRODUCT SPECTRUMS; REAL- TIME; TRACKING TECHNIQUES;

MAXIMUM LIKELIHOOD;

EID: 85159572977     PISSN: 22233881     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. Brown, J. and M. Puckette (1992). An efficient algorithm for the calculation of a Constant-Q transform. Journal of the Acoustical Society of America 92(5), 2698-2701.
2. Doval, B. and X. Rodet (1991). Fundamental frequency estimation using a new harmonic matching method. In Proceedings of the International Computer Music Association, pp. 555-558. Montreal, Canada.
3. Gold, B. and L. Rabiner (1969). Parallel processing techniques for estimating pitch periods of speech in the time domain. Journal of the Acoustical Society of America 46, 441-448.
4. Kobayashi, H. and T. Shimamura (Sept. 1995). A weighted autocorrelation method for pitch extraction of noisy speech. In Proceedings of the Acoustical Society of Japan, pp. 343-344. Urawa, Japan: Saitama University.
5. Master, A. (2000). Speech spectrum modeling from multiple sources. Master's thesis, Cambridge University, Engineering Dept., Cambridge, England.
6. Niesler, T. and T. Robinson. Speech analysis course handouts. Cambridge Univ. Enginnering Dept., 1999.
7. Noll, M. (1969). Pitch determination of human speech by the harmonic product spectrum, the harmonic sum spectrum, and a maximum likelihood estimate. In Proceedings of the Symposium on Computer Processing ing Communications, pp. 779-797. Polytechnic Institute of Brooklyn.