Enhanced Audio Signal Noise Removal using Five Level Fuzzy Haar Wavelet Transform - et al., Dr. G.M. Nasira (International Journal of Advanced Science and Technology, 2019)
This paper develops a novel idea on noise removal for audio signals specifically while performing voice pathology detection. Existing noise removal methods have commonly proven to be effective, so far these methods characteristically revels convinced unwanted features. Elimination or modification of the original audio feature of principal audio sound is a major issue. In case of voice pathology detection, it is very essential to perform denoising which will highly improve the classification accuracy. This work proposed a fuzzy enhanced approach which not only reduces the presence of noise but also used to recognize and preserve the richness of the audio spectrum. The proposed method using fuzzy wavelet noise reduction in audio signals is compare with ordinary wavelet denoising. Simulation results illustrates that the proposed work removes noise significantly and increases the classification of voice disorder with more accuracy.