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Hassan Dao
University Kuala Lumpur, Malaysia
Computer Science & IT Electrical & Electronics Engineering

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Single Channel Speech Enhancement using Wiener Filter and Compressive Sensing Amart Sulong; Teddy Surya Gunawan; Othman O Khalifa; Mira Kartiwi; Hassan Dao
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (608.922 KB) | DOI: 10.11591/ijece.v7i4.pp1941-1951

Abstract

The speech enhancement algorithms are utilized to overcome multiple limitation factors in recent applications such as mobile phone and communication channel. The challenges focus on corrupted speech solution between noise reduction and signal distortion. We used a modified Wiener filter and compressive sensing (CS) to investigate and evaluate the improvement of speech quality. This new method adapted noise estimation and Wiener filter gain function in which to increase weight amplitude spectrum and improve mitigation of interested signals. The CS is then applied using the gradient projection for sparse reconstruction (GPSR) technique as a study system to empirically investigate the interactive effects of the corrupted noise and obtain better perceptual improvement aspects to listener fatigue with noiseless reduction conditions. The proposed algorithm shows an enhancement in testing performance evaluation of objective assessment tests outperform compared to other conventional algorithms at various noise type conditions of 0, 5, 10, 15 dB SNRs. Therefore, the proposed algorithm significantly achieved the speech quality improvement and efficiently obtained higher performance resulting in better noise reduction compare to other conventional algorithms. 
Co-Authors Amart Sulong Mira Kartiwi Othman O Khalifa Teddy Surya Gunawan