关键词: 语音端点检测, 语带频谱, 最大特征值, 鲁棒性

Abstract: A Toeplitz de-noising method using the maximum eigenvalue is proposed for the voice activity detection at low SNR scenarios. This method uses the self-correlation sequence of speech bandwidth spectrum to construct a new symmetric Toeplitz matrix and to compute the largest eigenvalue, and the double decision thresholds in the largest eigenvalue are  applied in the decision framewok. Simulation results show that the presented algorithm is more effective in distinguishing speech from noise  and  has better robustness under various noisy environments. Compared with novel method of recurrence rate analysis, this algorithm shows lower wrong decision rate. The algorithm is of low computational complexity and is simple in real-time realization.

Key words: voice activity detection, speech bandwidth spectrum, maximum eigenvalue, robustness