Speech Signal Processing

Publication Details

Title Speech presence probability estimation based on temporal cepstrum smoothing
Authors Timo Gerkmann, Martin Krawczyk, Rainer Martin
Conference Int. Conf. Acoustics, Speech, Signal Processing (ICASSP)
Organization IEEE
Date Mar. 2010
Dallas, TX, USA


We propose a novel, robust estimator for the probability of speech presence at each time-frequency point in the short-time discrete Fourier domain. While existing estimators perform quite reliably in stationary noise environments, they usually exhibit a large false-alarm rate in nonstationary noise that results in a great deal of noise leakage when applied to a speech enhancement task. The proposed estimator overcomes this problem by temporally smoothing the cepstrum of the a posteriori signal-to-noise ratio (SNR), and yields considerably less noise leakage and low speech distortions in both, stationary and nonstationary noise as compared to state-of-the-art estimators. Especially in babble noise, this results in large SNR improvements.

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