Abstract: Based on the analysis of the power spectrum of speech signal and noise in high and low frequency band,a speech endpoint detection method under low SNR based on Bayesian decision of logarithmic power spectrum ratio in high and low frequency band is proposed.Firstly,the logarithm power spectrum ratio of speech signal and background noise in two different frequency bands is calculated respectively,and the statistical distribution is obtained according to the maximum likelihood estimation,and the optimal decision threshold is derived based on Bayesian decision criterion.When the signal is input,the log energy spectrum ratio of high and low frequency bands is calculated frame by frame and it is compared with the decision threshold to classify the speech and background noise,so as to realize the endpoint detection of speech signal.The experimental results show that,compared with the traditional double threshold detection method and spectral entropy detection method,the proposed method can detect speech endpoint more accurately under the condition of low SNR,and significantly improve the accuracy and speed of endpoint detection.

Key words: Bayesian decision, Logarithmic power spectrum ratio, Low SNR, Speech endpoint detection