陈胜, 徐岩, 王小军. 基于动态语音源数的自适应盲源分离算法[J]. 微电子学与计算机, 2015, 32(8): 19-23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.004
引用本文: 陈胜, 徐岩, 王小军. 基于动态语音源数的自适应盲源分离算法[J]. 微电子学与计算机, 2015, 32(8): 19-23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.004
CHEN Sheng, XU Yan, WANG Xiao-jun. Adaptive Blind Sources Separation Algorithm Based on Dynamic Speech Source Number[J]. Microelectronics & Computer, 2015, 32(8): 19-23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.004
Citation: CHEN Sheng, XU Yan, WANG Xiao-jun. Adaptive Blind Sources Separation Algorithm Based on Dynamic Speech Source Number[J]. Microelectronics & Computer, 2015, 32(8): 19-23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.004

基于动态语音源数的自适应盲源分离算法

Adaptive Blind Sources Separation Algorithm Based on Dynamic Speech Source Number

  • 摘要: 针对特定场合中语音信号源数动态变化的不确定性盲源分离问题,提出了拓展四阶累积量矩阵估计语音信号源数的自适应方法.该方法克服了传统盲源分离方法中事先假定已经确定语音信号源个数的前提下才能进行盲分离的不足,仅根据观测语音信号数与源信号数目的关系,自适应地选择盲源分离算法实现语音信号的分离.仿真实验结果表明,该语音源数估计的自适应盲源分离算法能有效地实现超定、适定与欠定情况下的语音信号的分离,而且分离效果及鲁棒性都较好.

     

    Abstract: Considering the number of uncertainty in dynamic speech signal's blind sources separation on particular occasions, expanding fourth-order cumulant matrix to estimate adaptively the number of speech signal sources is proposed. The method overcomes the shortage of traditional blind sources separation which presupposes the speech signal source number has been confirmed and adaptively chooses the corresponding blind sources separation algorithm to realize speech signal's separation only according to the relationship between number of observing speech signal and source speech signal. Simulation experimental results show that the algorithm can effectively realize overdetermind, posed-determind and underdetermind speech signal's separation with good separation performance and robust.

     

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