A cepstrum-based preprocessing and postprocessing for speech enhancement in adverse environments

摘要

This paper proposes a cepstrum-based preprocessing and postprocessing algorithm for single-channel speech enhancement. The cepstrum-based preprocessing scheme is applied to reduce the impact of the voiced speech on estimating the noise power spectral density (NPSD), which results in avoiding overestimating the NPSD by eliminating harmonic components of the voiced speech when tracking non-stationary noise components. The cepstrum-based postprocessing scheme is used to suppress both some non-stationary noise components and the annoying musical noise without introducing audible speech distortion. Experimental results show that the proposed algorithm could track non-stationary noise effectively without overestimating the NPSD. Moreover, the proposed algorithm achieves better performance in terms of both the segmental signal-to-noise-ratio improvement and the PESQ improvement.