An improved speech enhancement approach based on combination of compressed sensing and Kalman filter

This paper reviews some existing Speech Enhancement techniques and also proposes a new method for enhancing the speech by combining Compressed Sensing and Kalman filter approaches. This approach is based on reconstruction of noisy speech signal using Compressive Sampling Matching Pursuit (CoSaMP) algorithm and further enhanced by Kalman filter. The performance of the proposed method is evaluated and compared with that of the existing techniques in terms of intelligibility and quality measure parameters of speech. The proposed algorithm shows an improved performance compared to Spectral Subtraction, MMSE, Wiener filter, Signal Subspace, Kalman filter in terms of WSS, LLR, SegSNR, SNRloss, PESQ and overall quality.