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The Scientific World Journal
Volume 2013, Article ID 435729, 8 pages
Research Article

Robustness of Auditory Teager Energy Cepstrum Coefficients for Classification of Pathological and Normal Voices in Noisy Environments

Signal Processing Laboratory, Physics Department, Sciences Faculty of Tunis, University of Tunis ElManar, 1060 Tunis, Tunisia

Received 31 March 2013; Accepted 8 May 2013

Academic Editors: E. P. Ong and L. Silva

Copyright © 2013 Lotfi Salhi and Adnane Cherif. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • S. Emerald Shia, and T. Jayasree, “Detection of pathological voices using discrete wavelet transform and artificial neural networks,” 2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), pp. 1–6, . View at Publisher · View at Google Scholar
  • Aluisio I. R. Fontes, Pedro T. V. Souza, Adrião D. D. Neto, Allan de M. Martins, and Luiz F. Q. Silveira, “Classification System of Pathological Voices Using Correntropy,” Mathematical Problems in Engineering, vol. 2014, pp. 1–7, 2014. View at Publisher · View at Google Scholar
  • Laureano Moro-Velázquez, Jorge Andrés Gómez-García, Juan Ignacio Godino-Llorente, and Gustavo Andrade-Miranda, “Modulation Spectra Morphological Parameters: A New Method to Assess Voice Pathologies according to the GRBAS Scale,” BioMed Research International, vol. 2015, pp. 1–13, 2015. View at Publisher · View at Google Scholar