朱建伟, 孙水发, 但志平, 雷帮军. 基于子带二次谱熵的语音端点检测[J]. 微电子学与计算机, 2011, 28(3): 77-80.
引用本文: 朱建伟, 孙水发, 但志平, 雷帮军. 基于子带二次谱熵的语音端点检测[J]. 微电子学与计算机, 2011, 28(3): 77-80.
ZHU Jian-wei, SUN Shui-fa, DAN Zhi-ping, LEI Bang-jun. Voice Activity Detection Based on Sub-band Reprocessed Pectrum Entropy[J]. Microelectronics & Computer, 2011, 28(3): 77-80.
Citation: ZHU Jian-wei, SUN Shui-fa, DAN Zhi-ping, LEI Bang-jun. Voice Activity Detection Based on Sub-band Reprocessed Pectrum Entropy[J]. Microelectronics & Computer, 2011, 28(3): 77-80.

基于子带二次谱熵的语音端点检测

Voice Activity Detection Based on Sub-band Reprocessed Pectrum Entropy

  • 摘要: 为了提高在强噪声环境下语音端点检测的准确度,提出基于子带二次谱熵的端点检测算法.该算法把子带二次谱熵作为端点检测新的特征参数,首先计算每帧语音信号的二次谱,再多子带分析,计算二次谱熵;引入顺序统计滤波对二次谱熵平滑处理;将有限状态机判别方法与子带二次谱熵相合,形成新的语音/噪声判别算法,有效地解决单门限法易出现的两类误判.实验表明:与传统的两种方法相比,提出的端点检测算法具有准确性高、抗噪性强等优点.

     

    Abstract: Voice activity detection (VAD) in strong noise environments is improved by an algorithm based on subband reprocessed spectrum entropy (BRSE). As a new feature parameter for VAD, the reprocessed spectrum is calculated firstly, and reprocessed spectrum entropy is then calculated with multi-subband analysis. The order statistics filter is selected to smooth the BRPE. A new voice / noise discrimination algorithm is proposed by combining the finite state machine (FSM) with BRSE. The misdetections caused by single-threshold are reduced greatly. Experimental results show that the proposed algorithm has higher accuracy and stronger robustness than other two methods.

     

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