A new robust forward BSS adaptive algorithm based on automatic voice activity detector for speech quality enhancement

Author:

Zoulikha Meriem,Djendi Mohamed

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Reference47 articles.

1. Albouy, B., & Deville, Y. (2003). Alternative structures and power spectrum criteria for blind segmentation and separation of convolutive speech mixtures. In 4th international symposium on independent component analysis and blind signal separation (ICA) (pp. 361–366), Nara.

2. Al-Kindi, M. J., & Dunlop, J. (1989). Improved adaptive noise cancellation in the presence of signal leakage on the noise reference channel. Signal Process, 17(3), 241–250.

3. Araki, S., Makino, S., Aichner, R., Nishikawa, T., & Saruwatari, H. (2003) Subband based blind source separation with appropriate processing for each frequency band. In 4th international symposium on independent component analysis and blind signal separation (pp. 499–504). IEEE ICA 2003, Nara.

4. Bendoumia, R., & Djendi, M. (2014). Variable step-sizes new efficient two-channel backward algorithm for speech intelligibility enhancement: A subband approach. Applied Acoustics, 76, 209–222.

5. Bouquin-Jeannès, R. L., Azirani, A. A., & Faucon, G. (1997). Enhancement of speech degraded by coherent and incoherent noise using a cross-spectral estimator. IEEE Transactions on Speech and Audio Processing, 5, 484–487.

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