Speech Enhancement Using Compressed Sensing-based method

A procedure based on compressed sensing (CS) is proposed for speech enhancement. The latter is Prior-noise-estimation free. This approach is motivated by the fact that CS allows the recovery of only the sparse signal in the presence of non-sparse signal (noise). An application to an Arabic speech signal corrupted with white Gaussian noise is studied. Comparison of CS-based enhancement with three state-of-the-art methods is performed in terms of segmental SNR, root mean square error, and perceptual evaluation of speech quality (PESQ); and proved promising performances.