  In this paper, for real time enhancement of noisy speech, a method of
threshold determination based on modeling of Teager energy (TE) operated
perceptual wavelet packet (PWP) coefficients of the noisy speech and noise by
an Erlang-2 PDF is presented. The proposed method is computationally much
faster than the existing wavelet packet based thresholding methods. A custom
thresholding function based on a combination of mu-law and semisoft
thresholding functions is designed and exploited to apply the statistically
derived threshold upon the PWP coefficients. The proposed custom thresholding
function works as a mu-law or a semisoft thresholding function or their
combination based on the probability of speech presence and absence in a
subband of the PWP transformed noisy speech. By using the speech files
available in NOIZEUS database, a number of simulations are performed to
evaluate the performance of the proposed method for speech signals in the
presence of Gaussian white and street noises. The proposed method outperforms
some of the state-of-the-art speech enhancement methods both at high and low
levels of SNRs in terms of standard objective measures and subjective
evaluations including formal listening tests.
