Design of the Noise Suppressor Using the Perceptual Model and Wavelet Packet Transform

In this paper, we propose the noise suppressor with the perceptual model and wavelet packet transform. The objective is to enhance speech corrupted colored or non-stationary noise. If corrupted noise is colored, subband approach would be more efficient than whole band one. To avoid serious residual noise and speech distortion, we must adjust the Wavelet Coefficient Threshold (WCT). In this paper, the subband is designed matching with the critical band and WCT is adapted noise masking threshold (NMT) and segmental signal to noise ratio (seg_SNR). Consequently, it has similar performance with EVRC in PESQ-MOS. But it's better than wavelet packet transform using universal threshold about 0.289 in PESQ-MOS. The improtant thing is that it's more useful than EVRC in coded speech. In coded speech, PESQ-MOS is higher than EVRC about 0.23.