Robustness of Auditory Teager Energy Cepstrum Coefficients for Classification of Pathological and Normal Voices in Noisy Environments
This paper focuses on a robust feature extraction algorithm for automatic classification of pathological and normal voices in noisy environments. The proposed algorithm is based on human auditory processing and the nonlinear Teager-Kaiser energy operator. The robust features which labeled Teager Ene...
Saved in:
| Main Authors: | Lotfi Salhi, Adnane Cherif |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/435729 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Investigation of Noisy-to-noisy Voice Conversion Performance in Various Noisy Conditions
by: Chao Xie, et al.
Published: (2025-01-01) -
Noise-Robust Local Ternary Pattern Center for Noisy Texture Classification
by: Farhan A. Alenizi, et al.
Published: (2025-01-01) -
Robust multi-label surgical tool classification in noisy endoscopic videos
by: Adnan Qayyum, et al.
Published: (2025-02-01) -
ANALYSIS OF ELECTROENCEPHALOGRAMS RHYTHMS BY MEANS OF NONLINEAR OPERATOR TEAGER-KAISER
by: A. O. Kozmidiadi, et al.
Published: (2019-06-01) -
PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network
by: Mingzhu Shi, et al.
Published: (2015-10-01)