Perceptual wavelet adaptive denoising of speech

This paper introduces a novel speech enhancement system based on a wavelet denoising framework. In this system, the noisy speech is first preprocessed using a generalized spectral subtraction method to initially lower the noise level with negligible speech distortion. A perceptual wavelet transform is then used to decompose the resulting speech signal into critical bands. Threshold estimation is implemented that is both time and frequency dependent, providing robustness to non-stationary and correlated noisy environments. Finally, to eliminate the “musical noise” artifact, we apply a modified Ephraim/Malah suppression rule to the thresholding operation adaptive denoising. Both objective and subjective experiments prove that the new speech enhancement system is capable of significant noise reduction with little speech distortion.