A new two-microphone Gauss-Seidel pseudo affine projection algorithm for speech quality enhancement

摘要

This study addresses the problem of speech quality enhancement by adaptive and nonadaptive filtering algorithms. The well-known two-microphone forward blind source separation (TM-FBSS) structure has been largely studied in the literature. Several two-microphone algorithms combined with TM-FBSS have been recently proposed. In this study, we propose 2 contributions: In the first, a new two-microphone Gauss-Seidel pseudo affine projection (TM-GSPAP) algorithm is combined with TM-FBSS. In the second, we propose to use the new TM-GSPAP algorithm in speech enhancement. Furthermore, we show the efficiency of the proposed TM-GSPAP algorithm in speech enhancement when highly noisy observations are available. To validate the good performances of our algorithm, we have evaluated the adaptive filtering properties in computational complexity and convergence speed performance by system mismatch criteria. A fair comparison with adaptive and non adaptive noise reduction algorithms are also presented. The adaptive algorithms are the well-known two-microphone normalized least mean square algorithm, and the recently published two-microphone pseudo affine projection algorithm. The non adaptive algorithms are the one-microphone spectral subtraction and the two-microphone Wiener filter algorithm. We evaluate the quality of the output speech signal in each algorithm by several objective and subjective criteria as the segmental signal-to-noise ratio, cepstral distance, perceptual evaluation of speech quality, and the mean opinion score. Finally, we validate the superior performances of the proposed algorithm with physically measured signals.