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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m4rdj3kwwfcbvfzkv6kcnagwtm" style="color: black;">International Journal of Research in Engineering and Technology</a>
Audio signals are corrupted with many types of distortions. Major audio distortions are categorized into Globalized and Localized distortions. Localized distortion includes clipping and clicks where only certain samples are affected and globalized distortions include broadband noise where complete bandwidth is consumed by noise. Audio restoration is a technique for giving back the audio signals from these distortions. In this paper, audio restoration techniques for removing clipping, clicks and<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.15623/ijret.2015.0410014">doi:10.15623/ijret.2015.0410014</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wj4ttvpk5be5lhkamjxqwdxeki">fatcat:wj4ttvpk5be5lhkamjxqwdxeki</a> </span>
more »... broadband noise are put forwarded. Recent approaches to solving audio restoration problem is with respect to sparse representation algorithms. Clipping distortion is addressed with a Sparse representation framework, it is treated as a reverse problem, where the distorted samples is estimated from the surrounding undistorted samples, they are embedded in frame based scheme, and reconstructed by using an overlap add method in conjunction with OMP algorithm and Gabor/DCT dictionary for modelling audio signals. Broadband denoising is done by using spectral subtraction and Click removal is done by using an adaptive filter method as the first step. Performance measures are done based on perception, average SNR calculation and defined parameter variations. This paper also targeting towards the software and hardware implementation of the restoration methods using TMS320C6713 DSK kit with help of tools mainly MATLAB and Code Composer studio.
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