Speech denoising using discrete wavelet packet decomposition technique
Mehmet Alper Oktar, Mokhtar Nibouche, Yusuf Baltacı · 2016
In this paper, a discrete wavelet packet transform algorithm is used for speech signal denoising. Both hard and soft thresholding are applied and noisy speech signal samples corrupted by white Gaussian noise from 0 dB to +15 dB are denoised in our experiments. Output SNR (Signal to Noise Ratio) values are calculated and compared with input SNR values using both types of thresholding methods. Soft thresholding method is observed to perform better than hard thresholding at all input SNR levels. Hard thresholding shows a maximum of 5.9 dB improvement whereas soft thresholding shows a maximum of 6.5 dB improvement as an output SNR value.