Speech Enhancement Based on Wavelet Transform and Improved Subspace Decomposition

Messaoud MAB, Bouzid A. Speech Enhancement Based on Wavelet Transform and Improved Subspace Decomposition. J Audio Eng Soc. 2015;63(12):990-1000. doi:10.17743/jaes.2015.0083

@article{Messaoud2015_18057,
  author = {Messaoud, Mohamed Anouar Ben and Bouzid, Aicha},
  title = {{Speech Enhancement Based on Wavelet Transform and Improved Subspace Decomposition}},
  journal = {Journal of the Audio Engineering Society},
  volume = {63},
  number = {12},
  pages = {990--1000},
  year = {2015},
  month = dec,
  publisher = {Audio Engineering Society},
  doi = {10.17743/jaes.2015.0083},
  url = {https://doi.org/10.17743/jaes.2015.0083}
}

TY  - JOUR
TI  - Speech Enhancement Based on Wavelet Transform and Improved Subspace Decomposition
AU  - Messaoud, Mohamed Anouar Ben
AU  - Bouzid, Aicha
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 63
IS  - 12
SP  - 990
EP  - 1000
PY  - 2015
DA  - 2015/12/06
DO  - 10.17743/jaes.2015.0083
UR  - https://doi.org/10.17743/jaes.2015.0083
PB  - Audio Engineering Society
LA  - en
AB  - The authors propose a new speech enhancement approach based on the application of the wavelet packet transform with an optimal decomposition. The approach uses the principal component analysis (PCA) and an improved version of the robust PCA by imposing the nonnegative factorization on the low-rank matrix. In order to detect noisy time–frequency zones, a subspace decomposition based post-processing technique was implemented. A number of simulations were then used to evaluate performance under various types of noise. Standard objective measures, as well as subjective evaluations, show that this approach outperforms the comparable speech enhancement methods for noise-corrupted speech at low levels of signal-to-noise ratios. The technique creates the least distortion in the enhanced speech while suppressing less noise than the on-line semi-supervised Nonnegative Matrix Factorization.
ER  -