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Title"An improved speech enhancement approach based on combination of compressed sensing and Kalman filter"
Publication TypeConference Paper
Year of Publication2015
AuthorsK. Naruka, O. P. Sahu
Conference Name2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)
Date PublishedDec
PublisherIEEE
ISBN Number978-1-4799-7849-6
Accession Number15870747
Keywordscompressed sensing, compressive sampling matching pursuit, CoSaMP algorithm, improved speech enhancement approach, Kalman filter, Kalman filters, least mean squares methods, Mathematical model, MMSE, Noise measurement, noisy speech signal reconstruction, objective measures, pubcrawl170104, signal reconstruction, signal subspace, Spectral Subtraction, Speech, speech enhancement, speech enhancement techniques, Wiener filter, Wiener filters
Abstract

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.
URLhttps://ieeexplore.ieee.org/document/7435699
DOI10.1109/ICCIC.2015.7435699
Citation Key7435699
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