Speech endpoints detection based on improved HHT in strong noisy environment

In order to improve correctness of Voice Activity Detection(VAD)system under low Signal Noise Rate(SNR),an improved approach of VAD based on Hilbert-Huang Transformation(HHT)is proposed.Every frame of signal is decomposed into finite Intrinsic Mode Functions(IMFs)by Empirical Mode Decomposition(EMD).Then all IMFs except the first one are filtered by a bandpass filter whose passband is from 250 Hz to 3 500 Hz to choose the parts of an IMF.And then useful IMFs are weighted with different weights and transformed by Hilbert Transformation(HT)to get energy value.After that,noise threshold is evaluated through the analysis of noise feature.On the basis of threshold,the starting points and ending points are seeked out on Hilbert energy specturm.Simulation results show that the presented method not only can improve correctness of VAD,but also have strong robustness under low SNR.