Abstract
In speech processing, pitch period is a very important characteristic parameter, but accurate pitch is not easy to be detected, especially in noisy environments, because speech signal is nonstationary and quasiperiodical. This paper describes a new method based upon mathematical morphology and weighted modified autocorrelation function(MACF). Morphology is a nonlinear method which is based on set-theoretical algebra, we can form kinds of morphology filters using different structuring elements. Weighted MACF modifies traditional autocorrelation method with reciprocal of AMDF. Experiments show that the combination of these algorithms provides robust performance and makes better result in noisy speech pitch detection.
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References
Oh, K.A., Un, C.K.: A performance comparison of pitch extraction algorithm for noisy speech. In: Proc. IEEE Int. Conf. on ASSP, pp. 18B4.1-18B4.4 (1984)
Hai-hua, C., Tian-shu, Q., Shu-xun, W.: Speech Signal Fundamental Frequency Detection Based on Wavelet Transform. Journal of Jilin University Engineering and Technology Edition 32(2), 68–72 (2002)
Ruizhen, Z., Guoxiang, S.: A Fast Algorithm for Pitch Detection with Wavelet Tansform. Electronic Science and Technology (1), 16–19 (1998)
Maragos, P., Schafer, R.W.: Morphological Filters - Part I and II Their Relations to Median, Order-Statistic, and Stack Filters. IEEE Trans. ASSP 35(8), 1170–1184 (1987)
Serra, J.: Image Analysis and Mathematical Morphology. Academic, New York (1982)
Xiaoqun, Z., Guangyan, W.: A New Approach of the Morphology Filter for Pitch Contrail Smoothing of Chinese Tone. Signal Processing 19(4), 354–357 (2003)
Hansen, J.H.L.: Morphology Constrained Feature Enhancement with Adaptive Cepstral Compensation(MCE-ACC) for Speech Recognition in Noise and Lombard Effect. IEEE Transaction on Speech and Audio Processing, l. 2(4), 598–614 (1994)
Boseorth, J.H.: Morphological local monotonicity for multiscale image segmentation. Ph.D Paper, University of Virginia (2002)
Hung, W.: Use of fuzzy weighted autocorrelation function for pitch extraction from noisy speech. Electronics letters 38(19), 1148–1150 (2002)
Tetsuya, S., Hajime, K.: Weighted autocorrelation for pitch extraction of noisy speech. IEEE Trans Speech Audio Process 9(7), 727–730 (2001)
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© 2004 Springer-Verlag Berlin Heidelberg
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Wang, X., Tang, H., Zhao, X. (2004). Noisy Speech Pitch Detection Based on Mathematical Morphology and Weighted MACF. In: Li, S.Z., Lai, J., Tan, T., Feng, G., Wang, Y. (eds) Advances in Biometric Person Authentication. SINOBIOMETRICS 2004. Lecture Notes in Computer Science, vol 3338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30548-4_68
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DOI: https://doi.org/10.1007/978-3-540-30548-4_68
Publisher Name: Springer, Berlin, Heidelberg
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