Abstract
Wavelet packet transform has been progressively applied in removing the additive white Gaussian noise. By using soft thresholding function, it performs well in enhancing the corrupted speech. However, it suffers from serious residual noise and speech distortion. In this paper, we propose a method based on critical-band decomposition which converts a noisy signal into wavelet coefficients (WCs), and enhances the WCs by subtracting a threshold from noisy WCs in each subband. The threshold of each subband is adapted according to the segmental SNR (SegSNR) and the noise masking threshold. Thus residual noise can be efficiently suppressed for a speech-dominated frame. In a noise-dominated frame, the background noise can be almost removed by adjusting the wavelet coefficient threshold (WCT) according to the SegSNR. Speech distortion can be reduced by decreasing the WCT in speech-dominated subbands. The proposed method can effectively enhance noisy speech which is infected by colored-noise. Its performance is better than other wavelet-based speech enhancement methods in our experiments.
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