Speech enhancement with an adaptive Wiener filter

This paper proposes an adaptive Wiener filtering method for speech enhancement. This method depends on the adaptation of the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance. It is implemented in the time M.A. Abd El-Fattah · M.I. Dessouky · A.M. Abbas · S.M. Diab · S.M. El-Rabaie · F.E. Abd El-samie (B) Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt e-mail: [email protected] M.A. Abd El-Fattah e-mail: [email protected] M.I. Dessouky e-mail: [email protected] A.M. Abbas e-mail: [email protected] S.M. Diab e-mail: [email protected] S.M. El-Rabaie e-mail: [email protected] W. Al-Nuaimy Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool L69 3GJ, UK e-mail: [email protected] S.A. Alshebeili Electrical Engineering Department, KACST-TIC in Radio Frequency and Photonics for the e-Society (RFTONICS), King Saud University, Riyadh, Kingdom of Saudi Arabia e-mail: [email protected] F.E. Abd El-samie KACST-TIC in Radio Frequency and Photonics for the e-Society (RFTONICS), King Saud University, Riyadh, Kingdom of Saudi Arabia domain rather than in the frequency domain to accommodate for the time-varying nature of the speech signals. The proposed method is compared to the traditional frequencydomain Wiener filtering, spectral subtraction and wavelet denoising methods using different speech quality metrics. The simulation results reveal the superiority of the proposed Wiener filtering method in the case of Additive White Gaussian Noise (AWGN) as well as colored noise.