Pitch estimation of noisy speech signals using EMD-fourier based hybrid algorithm.
ABSTRACT 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: A technique for estimating the pitch of a speech waveform is developed. It fits a harmonic set of sine waves to the input data using a mean-squared-error (MSE) criterion. By exploiting a sinusoidal model for the input speech waveform, a pitch estimation criterion is derived that is inherently unambiguous, uses pitch-adaptive resolution, uses small-signal suppression to provide enhanced discrimination, and uses amplitude compression to eliminate the effects of pitch-formant interaction. The normalized minimum mean squared error proves to be a powerful discriminant for estimating the likelihood that a given frame of speech is voicedAcoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on; 05/1990
Conference Paper: Real-time robust pitch detector[Show abstract] [Hide abstract]
ABSTRACT: The authors propose a cumulant-based method to perform voice-unvoiced decision and pitch period estimation. The approach is based on the nature of excitation for different states of speech. The authors accomplished this goal by analyzing cumulant-related time sequences obtained via nonlinear processing of the speech signal. Experimental results indicating the performance of the proposed method, especially in the pitch estimation problem in which there are high power harmonics are presentedAcoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on; 04/1992
- INTERSPEECH 2007, 8th Annual Conference of the International Speech Communication Association, Antwerp, Belgium, August 27-31, 2007; 01/2007