Speech Denoising Using Wavelet Transforms

Kamya Dubey; Prof. Vikas Gupta

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.

Select Volume / Issues:

• Volume 4 Issue 5, Sept. 2013

Year:

2013

Type of Publication:

Article

Keywords:

Speech Denoising; CWT; DWT; Detailed Coefficients; Approximation Coefficients; MRA

Journal:

IJECCE

Volume:

4

Number:

5

Pages:

1382-1385

Month:

September