Matrix quantization based time-varying filter speech enhancement

Speech spectral continuity is important in speech perception. We explore in this paper, the use of matrix quantization (MQ) to model spectral contours and impose time continuity in presence of noise. It is found that contours fitted over an optimum duration of 90-100 msec greatly improve speech quality. We show that Wiener filters derived from spectral contour matrices must operate in a time-varying manner and also propose a technique to achieve it through interpolation and STFT based reconstruction. In addition to conventional spectral distortion measures, we compare spectral transition measure profiles of clean and enhanced speech which indicate that MQ codebooks combined with time-varying Wiener filtering improve speech enhancement even at 0 dB SNR.