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Proceedings Paper

Speech signal denoising with wavelet-transforms and the mean opinion score characterizing the filtering quality
Author(s): Alauldeen S. Yaseen; Alexey N. Pavlov; Alexander E. Hramov
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Paper Abstract

Speech signal processing is widely used to reduce noise impact in acquired data. During the last decades, wavelet-based filtering techniques are often applied in communication systems due to their advantages in signal denoising as compared with Fourier-based methods. In this study we consider applications of a 1-D double density complex wavelet transform (1D-DDCWT) and compare the results with the standard 1-D discrete wavelet-transform (1DDWT). The performances of the considered techniques are compared using the mean opinion score (MOS) being the primary metric for the quality of the processed signals. A two-dimensional extension of this approach can be used for effective image denoising.

Paper Details

Date Published: 17 March 2016
PDF: 6 pages
Proc. SPIE 9707, Dynamics and Fluctuations in Biomedical Photonics XIII, 970719 (17 March 2016); doi: 10.1117/12.2211384
Show Author Affiliations
Alauldeen S. Yaseen, Saratov State Univ. (Russian Federation)
Univ. of Technology (Iraq)
Alexey N. Pavlov, Saratov State Univ. (Russian Federation)
Saratov State Technical Univ. (Russian Federation)
Institute of Radio-Engineering and Electronics of Russian Academy of Sciences (Russian Federation)
Alexander E. Hramov, Saratov State Technical Univ. (Russian Federation)
Saratov State Univ. (Russian Federation)
Institute of Radio-Engineering and Electronics of Russian Academy of Sciences (Russian Federation)


Published in SPIE Proceedings Vol. 9707:
Dynamics and Fluctuations in Biomedical Photonics XIII
Valery V. Tuchin; Kirill V. Larin; Martin J. Leahy; Ruikang K. Wang, Editor(s)

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