提出一种采用累积量矩阵的最大奇异值来实现语音端点检测的方法，并引入一种自适应的实现方法。
The proposed method uses the maximum singular value of an cumulant matrix to distinguish between voiced parts of the speech signal and noise.
针对语音信号的弱稀疏性，提出一种新的基于混合矩阵估计的欠定语音盲分离方法。
This paper proposes a new method based on mixing matrix estimation for underdetermined blind speech separation, aiming at speech signals under weak sparseness.
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