An immunological approach based on the negative selection algorithm for real noise classification in speech signals

@inproceedings{Abreu2017AnIA,
  title={An immunological approach based on the negative selection algorithm for real noise classification in speech signals},
  author={Caio Cesar Enside de Abreu and Marco A. Q. Duarte and Francisco Chong Villarreal},
  year={2017}
}
Abstract This paper presents a new approach to detect and classify background noise in speech sentences based on the negative selection algorithm and dual-tree complex wavelet transform. The energy of the complex wavelet coefficients across five wavelet scales are used as input features. Afterward, the proposed algorithm identifies whether the speech sentence is, or is not, corrupted by noise. In the affirmative case, the system returns the type of the background noise amongst the real noise… CONTINUE READING