Pitch estimation of noisy speech signals using EMD-fourier based hybrid algorithm

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.