Speech Signal Processing

Publication Details

Title A Novel A Priori SNR Estimation Approach Based on Selective Cepstro-Temporal Smoothing
Authors Colin Breithaupt, Timo Gerkmann, Rainer Martin
Conference Int. Conf. Acoustics, Speech, Signal Processing (ICASSP)
Organization IEEE
Date Apr. 2008
Las Vegas, NV, USA


While state-of-the-art approaches obtain an estimate of the a priori SNR by adaptively smoothing its maximum likelihood estimate in the frequency domain, we selectively smooth the maximum likeli hood estimate in the cepstral domain. In the cepstral domain the noisy speech signal is decomposed into coefficients related mainly to the speech envelope, the excitation, and noise. As in the cepstral domain coefficients that represent speech can be robustly determined, we can apply little smoothing to speech coefficients and strong smoothing to noise coefficients. Thus, speech components are preserved and musical noise is suppressed. In speech enhancement experiments we obtain consistent improvements over the well known decision-directed approach.

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