Abstract: Combined Empirical Mode Decomposition（EMD） of Hilbert-Huang Transform（HHT） with Recurrence Plot（RP） method，a new algorithm of speech endpoint detection is proposed.In this algorithm，different Intrinsic Mode Function（IMF） is filtered on the time scale of soft threshold by EMD and multi-scale features based on speech and noise at first.Then，through using the RP method of nonlinear dynamic behavior，quantitative statistical analysis of the deterministic recursive to carry out speech endpoint detection.Simulation results show that the method has strong ability of non-steady-state analysis of dynamic change，more accurately than the traditional methods to extract the start and end point of speech signal and better robustness in low SNR environment.

摘要： 结合Hilbert-Huang变换中的经验模态分解（EMD）和递归图（RP）法，提出了一种新的语音端点检测算法。该算法首先基于语音和噪声通过经验模态分解及其多尺度特征，在不同的固有模态函数（IMF）上进行软阈值时间尺度滤波处理，然后采用非线性动力学行为中的递归图法，定量统计递归分析中的确定性进行语音端点检测。仿真结果表明，该方法具有很强的非稳态动态变化分析能力，在低信噪比环境下较传统方法能更准确提取出语音信号的起止点，鲁棒性好。