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This paper shows the importance of the optimal smoothing scheme in Microphone Array Post-Filtering(MAPF) under a combined Deterministic-Stochastic Hybrid Model(DSHM).We reveal that some of the well-known MAPF algorithms may cause serious speech distortion without using the optimal smoothing scheme,which is resulted from oversmoothing the raw periodogram over time.Using a minimum conditional mean square error criterion,we derive the optimal smoothing factor under the DSHM,where the Deterministic-to-Stochastic-Ratio(DSR) and the stationarity determine the value of the optimal smoothing factor.The optimal smoothing scheme is applied to the Tran-sient-Beam-to-Reference-Ratio(TBRR)-based MAPF algorithm and experimental results show its better performance in terms of both the Log-Spectral Distance(LSD) and the Perceptual Evaluation of Speech Quality(PESQ).
This paper shows the importance of the optimal smoothing scheme in Microphone Array Post-Filtering (MAPF) under a combined Deterministic-Stochastic Hybrid Model (DSHM). We reveal that some of the well-known MAPF algorithms may cause serious speech distortion without using the optimal smoothing scheme, which is resulted from oversmoothing the raw periodogram over time. Using a minimum conditional mean square error criterion, we derive the optimal smoothing factor under the DSHM, where the Deterministic-to-Stochastic-Ratio (DSR) and the stationarity determine the value of the optimal smoothing factor. The optimal smoothing scheme is applied to the Tran-sient-Beam-to-Reference-Ratio (TBRR) -based MAPF algorithm and experimental results show its better performance in terms of both the Log-Spectral Distance (LSD) and the Perceptual Evaluation of Speech Quality (PESQ).