Adaptive Cepstral Distance-based Voice Endpoint Detection of Strong Noise

Abstract

Abstract: In the case of noise interference,accuracy of speech endpoint detection using the traditional method dramati-cally declines.In order to effectively distinguish the speech signal and non-voice signal in strong background noise environment,this paper presented a strong noise speech endpoint detection method based on adaptive cepstral distance.The method introduces cepstral distance multiplier and the threshold increment coefficient.Different cepstral distance multipliers are used for different SNR and adaptive decision threshold method is used for voice activity detection.MATLAB simulation results show that,under different background noise and different SNR,the method for voice activity detection has high detection accuracy.Its detection is better than the traditional endpoint detection method,and is suitable for endpoint detection under strong background noise.

Key words: Cepstral distance,Adaptive decision threshold,Strong noise,Endpoint detection

ZHAO Xin-yan, WANG Lian-hong and PENG Lin-zhe. Adaptive Cepstral Distance-based Voice Endpoint Detection of Strong Noise[J].Computer Science, 2015, 42(9): 83-85.

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