Codebook constrained iterative and Parametric Wiener filter speech enhancement

In this paper a new iterative method of speech enhancement using Power Spectral Density (PSD) codebooks of clean speech and several types of noise, is proposed. The proposed algorithm estimates the PSDs of speech and noise of unknown nature and, evaluates the input Signal-to-Noise Ratio (SNR) by solving an over-determined set of equations. No Voice Activity Detection (VAD) or other means of noise spectral estimation such as minimum statistics is used. The pre-calculated codebooks are tree structured for the sake of speed of processing. The Wiener filter is used in the first instance because of its simplicity. A new variant of Parametric Wiener filter whose parameters are controlled by the skewness and kurtosis of the estimated clean speech and noise is also used to further suppress the noise. The results of employing these iterative algorithms are reported and compared for enhancement of noisy speech of different noise types and different input SNRs.