Pitch determination of noisy speech using higher order statistics

Abstract

The use of third-order statistics to determine the pitch of a speech signal and how they can eliminate the effect of a wide range of noises, including those generated by periodic sources, are shown. The proposed algorithm is based on the property that higher-order statistics can extract useful information about the statistics of voiced frames, and they can separate speech from noise. Third-order statistics are quite insensitive to most noises (Gaussian, sinusoidal, car noise, etc.) because these noises have a symmetric probability density function, and therefore their third-order cumulants are zero. The algorithm has been tested in noise-corrupted speech, at different levels of signal to noise ratio, and with different kinds of noise. The results show that this new algorithm gives in all the cases a much better estimation of the pitch than the conventional autocorrelation method.

Peer Reviewed

Postprint (published version)