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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© 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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