Generalized Postfilter for Speech Quality Enhancement

Abstract

Postfilters are commonly used in speech coding for the attenuation of quantization noise. In the presence of acoustic background noise or distortion due to tandeming operations, the postfilter parameters are not adjusted and the performance is, therefore, not optimal. We propose a modification that consists of replacing the nonadaptive postfilter parameters with parameters that adapt to variations in spectral flatness, obtained from the noisy speech. This generalization of the postfiltering concept can handle a larger range of noise conditions, but has the same computational complexity and memory requirements as the conventional postfilter. Test results indicate that the presented algorithm improves on the standard postfilter, as well as on the combination of a noise attenuation preprocessor and the conventional postfilter.