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Research Article | Open Access |

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
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 10 · Published 2016 · Cited by 6

DOI: https://doi.org/10.14569/IJACSA.2016.071026

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.

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How to Cite this Article

SAOUD, S., BOUSSELMI, S., NASER, M. B., & CHERIF, A. (2016). New Speech Enhancement based on Discrete Orthonormal Stockwell Transform. International Journal of Advanced Computer Science and Applications, 7(10). https://doi.org/10.14569/IJACSA.2016.071026

SAOUD, Safa, et al.. "New Speech Enhancement based on Discrete Orthonormal Stockwell Transform." International Journal of Advanced Computer Science and Applications, vol. 7, no. 10, 2016, https://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},
  volume    = {7},
  number    = {10},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Safa SAOUD and Souha BOUSSELMI and Mohamed BEN NASER and Adnane CHERIF},
  doi       = {10.14569/IJACSA.2016.071026},
  url       = {https://doi.org/10.14569/IJACSA.2016.071026}
}

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