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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

New Speech Enhancement based on Discrete Orthonormal Stockwell Transform

Author 1: Safa SAOUD
Author 2: Souha BOUSSELMI
Author 3: Mohamed BEN NASER
Author 4: Adnane CHERIF

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.071026

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 10, 2016.

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Abstract: S-transform is an effective time-frequency representation which gives simultaneous frequency and time distribution information alike the wavelet transforms (WT). However, the ST redundantly doubles the dimension of the original data set and the Discrete Orthonormal S-Transform (DOST) can decrease the redundancy of S-transform farther. So, this paper aims to propose a new method to remove additive background noise from noisy speech signal using DOST which supplies a multi-resolution analysis (MRA) spatial-frequency representation of image processing and signal analysis. Hence, the performances of the applied speech enhancement technique have been evaluated objectively and subjectively in comparison with respect to many other methods in four background noises at different SNR levels.

Keywords: MRA; Stockwell Transform; DOST; DWT; speech enhancement

Safa SAOUD, Souha BOUSSELMI, Mohamed BEN NASER and Adnane CHERIF, “New Speech Enhancement based on Discrete Orthonormal Stockwell Transform” International Journal of Advanced Computer Science and Applications(IJACSA), 7(10), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071026

@article{SAOUD2016,
title = {New Speech Enhancement based on Discrete Orthonormal Stockwell Transform},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071026},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071026},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {10},
author = {Safa SAOUD and Souha BOUSSELMI and Mohamed BEN NASER and Adnane CHERIF}
}


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