Cepstral Smoothing of Spectral Filter Gains for Speech Enhancement Without Musical Noise

Publication Details

Title Cepstral Smoothing of Spectral Filter Gains for Speech Enhancement Without Musical Noise
Authors Colin Breithaupt, Timo Gerkmann, Rainer Martin
Journal Signal Processing Letters
Organization IEEE
Date Dec. 2007


Many speech enhancement algorithms which modify short term spectral magnitudes of the noisy signal by means of adaptive spectral gain functions are plagued by annoying spectral outliers. In this letter we propose cepstral smoothing as a solution to this problem. We show that cepstral smoothing can effectively prevent spectral peaks of short duration that may be perceived as musical noise. At the same time cepstral smoothing preserves speech onsets, plosives, and quasi-stationary narrow-band structures like voiced speech. The proposed recursive temporal smoothing is applied to higher cepstral coefficients only, excluding those representing the pitch information. As the higher cepstral coefficients describe the finer spectral structure of the Fourier spectrum, smoothing them along time prevents single coefficients of the filter function from changing excessively and independently of their neighboring bins, thus suppressing musical noise. The proposed cepstral smoothing technique is very effective in non-stationary noise.

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