An effective speech preprocessing technique for normalized cross-correlation pitch extractor

A noise robust method for pitch estimation based on a new speech preprocessing technique is presented in this paper. The rectified dominant harmonic of the pre-filtered signal is used for preprocessing. The normalized crosscorrelation function and circular average magnitude difference function are used for pitch extraction. The performance of the proposed method is tested and compared with a recent method using the Keele pitch extraction reference database. Comparative results show that the proposed method can detect pitch with better accuracy for a wide range of signal-to-noise ratios (SNRs).

[1]  Aaron E. Rosenberg,et al.  A comparative performance study of several pitch detection algorithms , 1976 .

[2]  M. J. Cheng,et al.  Comparative performance study of several pitch detection algorithms , 1975 .

[3]  Gang Xu,et al.  Pitch estimation based on Circular AMDF , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4]  David A. Krubsack,et al.  An autocorrelation pitch detector and voicing decision with confidence measures developed for noise-corrupted speech , 1991, IEEE Trans. Signal Process..

[5]  A. Noll.  Cepstrum pitch determination. , 1967, The Journal of the Acoustical Society of America.

[6]  Stephen A. Zahorian,et al.  Yet Another Algorithm for Pitch Tracking , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[7]  M. Ross,et al.  Average magnitude difference function pitch extractor , 1974 .

[8]  Fabrice Plante,et al.  A pitch extraction reference database , 1995, EUROSPEECH.

[9]  Lawrence R. Rabiner,et al.  On the use of autocorrelation analysis for pitch detection , 1977 .

[10]  Hajime Kobayashi,et al.  Weighted autocorrelation for pitch extraction of noisy speech , 2001, IEEE Trans. Speech Audio Process..

[11]  Thomas F. Quatieri,et al.  Pitch estimation and voicing detection based on a sinusoidal speech model , 1990, International Conference on Acoustics, Speech, and Signal Processing.