Traditional short-time spectral attenuation (STSA) speech enhancement algorithms are ineffective in the presence of highly nonstationary noise due to difficulties in the accurate estimation of the local noise spectrum. With a view to improve the speech quality in the presence of random noise bursts, characteristic of many environmental sounds, a simple postprocessing scheme is proposed that can be applied to the output of an STSA speech enhancement algorithm. The postprocessing algorithm is based on using spectral properties of the noise in order to detect noisy time-frequency regions which are then attenuated using a SNR-based rule. A suitable suppression rule is developed that is applied to the detected noisy regions so as to achieve significant reduction of noise with minimal speech distortion. The post-processing method is evaluated in the context of two well-known STSA speech enhancement algorithms and experimental results demonstrating improved speech quality are presented for a data set of real noise samples. (c) 2005
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