Enhancement of speech signals under multiple hypotheses using an indicator for transient noise presence

In this paper, we formulate a speech enhancement problem under multiple hypotheses, assuming an indicator or detector for the transient noise presence is available in the short-time Fourier transform (STFT) domain. Hypothetical presence of speech or transient noise is considered in the observed spectral coefficients, and cost parameters control the trade-off between speech distortion and residual transient noise. An optimal estimator, which minimizes the mean-square error of the log-spectral amplitude, is derived, while taking into account the probability of erroneous detection. Experimental results demonstrate the improved performance in transient noise suppression, compared to using the optimally-modified log-spectral amplitude estimator.