关键词: 语音端点检测, 迭代维纳滤波, 子带频谱熵, 自适应处理, 鲁棒性

Abstract: This paper proposes an effective real-time voice activity detection algorithm in various noisy environments in the acoustical signal filting.It makes the iterative methods of estimating the noise power spectrum.The speech spectrum is filted with iterative Wiener method.The filting spectrum is divided into several subbands and the spectral entropy of each subband is estimated.Median filters are applied to a sequence of the subband entropies to obtain the spectral entropy of each frame.The speech/noise classification is based on the spectral entropy.The experimental results show that the proposed algorithm can distinguish speech from noise effectively and improve the performance of automatic speech recognition system significantly.It is proved to be robust under various noisy environments.The algorithm is of low computational complexity which is suitable for real-time speech recognition system application．

Key words: voice activity detection, iterative Wiener filtering, subband spectrum entropy, adaptive processing, robustness