Speech Signal Processing

Publication Details

Title Improved A Posteriori Speech Presence Probability Estimation Based on a Likelihood Ratio with Fixed Priors
Authors Timo Gerkmann, Colin Breithaupt, Rainer Martin
Journal Trans. Audio, Speech and Language Processing
Organization IEEE
Date Jul. 2008


In this contribution we present an improved estimator for the speech presence probability at each time-frequency point in the short-time Fourier-transform domain. In contrast to existing approaches this estimator does not rely on an adaptively estimated and thus signal dependent a priori signal-to-noise ratio estimate. It therefore decouples the estimation of the speech presence probability from the estimation of the clean speech spectral coefficients in a speech enhancement task. Using both a fixed a priori signal-to-noise ratio and a fixed prior probability of speech presence, the proposed a posteriori speech presence probability estimator achieves probabilities close to zero for speech absence and probabilities close to one for speech presence. While state-of-the-art speech presence probability estimators use adaptive prior probabilities and signal-to-noise ratio estimates we argue that these quantities should reflect true a priori information that shall not depend on the observed signal. We present a detection theoretic framework for determining the fixed a priori signal-to-noise ratio. The proposed estimator is conceptually simple and yields a better trade-off between speech distortion and noise leakage than state-of-the-art estimators.

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