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Optimal smoothing for microphone array post-filtering under a combined deterministic-stochastic hybrid model

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Journal of Electronics (China)

Abstract

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 Transient-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).

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Authors and Affiliations

  1. Communication Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing, 100190, China

    Xiaohu Hu, Chengshi Zheng & Xiaodong Li

  2. Institute of Acoustics, Chinese Academy of Sciences, Beijing, 100190, China

    Chengshi Zheng

Authors
  1. Xiaohu Hu
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  2. Chengshi Zheng
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  3. Xiaodong Li
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Corresponding author

Correspondence to Chengshi Zheng.

Additional information

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

Communication author: Zheng Chengshi, born in 1980, male, Assistant Professor.

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Hu, X., Zheng, C. & Li, X. Optimal smoothing for microphone array post-filtering under a combined deterministic-stochastic hybrid model. J. Electron.(China) 28, 524–530 (2011). https://doi.org/10.1007/s11767-012-0778-y

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  • DOI: https://doi.org/10.1007/s11767-012-0778-y

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