摘要
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）.
基金
Supported by the National Natural Science Foundation of China (No. 61072123)
