Speech Denoising Using Wavelet Transforms

Audio signal denoising has been and still is a major issue. Wavelet has localization feature along with its time-frequency resolution properties which makes it suitable for analyzing non-stationary signals such as speech signals. In this paper denoising is done using coiflet and daubechies wavelet techniques and the original signal is completely reconstructed. Better estimation of the amplitude is also obtained in wavelet based denoising. PSD value is compared for FFT and wavelets and it has been found that wavelet shows better results than FFT.