Enhancement of speech using bark-scaled wavelet packet decomposition
Israel Cohen · 2001
In this paper, ve propose a speech enhancement system, vhich integrates a bark-scaled vavelet packet decompo- sition (BS-WPD), a soft-decision gain modification and a "magnitude" decision-directed estimation technique. The BS-WPD provides an overcomplete auditory representation, having a higher frequency resolution than the critical band decomposition. Speech is estimated by Wiener filtering in the vavelet packet domain, modified by the signal presence probability. We introduce a "magnitude" decision-directed estimator for the variance of speech, vhich is closely related to the decisiondirected estimator of Ephraim and Malah. This estimator achieves, in the established process, a better tradeoff betveen noise reduction and signal distortion. The proposed enhancement algorithm is tested vith various noise types, and compared to a conventional log-spectral amplitude estimator. We shov that noise can be further suppressed, vhile preserving its natural structure and the intelligibility and quality of the speech components.