Pitch estimation of noisy speech signals using EMD-fourier based hybrid algorithm.
DOI: 10.1109/ISCAS.2010.5537054 Conference: International Symposium on Circuits and Systems (ISCAS 2010), May 30 - June 2, 2010, Paris, France
This paper focuses on a pitch estimation method of noisy speech signal using the combination of empirical mode decomposition (EMD) and discrete Fourier transform (DFT). The noisy speech signal is filtered within the range of fundamental frequency. Normalized autocorrelation function (NACF) is computed from the pre-filtered noisy speech signal. The NACF is decomposed by EMD to generate a finite number of band limited signal called Intrinsic Mode Function (IMF). DFT is applied to NACF to determine the dominant frequency of the analyzing speech frame. The IMF with fundamental period closest to that of the dominant frequency is selected as the target IMF containing the fundamental period. The performance of the proposed pitch estimation method is compared in terms of gross pitch error (GPE) with the recent algorithms. The experimental results show that the proposed one performs better for noisy and clean speech signals.
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ABSTRACT: We have proposed F0 estimation based on time-varying complex AR (TV-CAR) speech analysis in which F0 is estimated using an weighted auto-correlation function for complex-valued residual signal calculated by the estimated time-varying complex-valued parameter for analytic signal. On the other hand, Zero Frequency Resonance (ZFR) has been proposed and it has been reported that the ZFR can estimate more accurate F0. The ZFR employs Zero Frequency Filtering (ZFF) for Hilbert envelope(HE) of LP residual to emphasize the resonance at zero frequency. In this paper, the ZFR based on TV-CAR speech analysis is proposed to estimate more accurate F0. In the proposed method, the HE is calculated with complex LP residual estimated by the complex parameters for analytic signal. The ZFR signal is calculated from the HE. The ZFR signal is used for the weighted auto-correlation to estimate F0. We have conducted the evaluation of F0 estimation using Keele Pitch database. The experimental results show that LP residual-based ZFR method performs best.Circuits and Systems (ISCAS), 2012 IEEE International Symposium on; 01/2012
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