Speech Signal Processing
|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) |
|Place ||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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