We propose a noise reduction scheme in order to correct vocal disorders. The filter is based on concepts and tools originated from nonlinear time series analysis and deterministic chaos theory field. This work can provide a better understanding of voice dysfunctions, with a clear advantage for subjects a&# 11;ected by vocal pathologies. With similars tools, indeed, physicians can perform better surgical interventions and researchers can build devices to improve voice quality also without a surgigal treatment. We describe the filter and the idea of geometric signal classification in a feature space in order to visualize the effect of the noise reduction step. We focus our attention on patients a&# 11;ected by T1A glottis cancer and describe which kind of corrections are necessary to improve the quality of the voice, i.e. to move the feature vector from the sick cluster to the healthy zone.
Index Terms. Chaos Theory, Nonlinear Noise Reduction, Feature Space, Vocal Disorders
Cite as: Matassini, L., Manfredi, C. (2001) Noise reduction for vocal pathologies. Proc. Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA 2001), 156-162
@inproceedings{matassini01_maveba,
author={Lorenzo Matassini and Claudia Manfredi},
title={{Noise reduction for vocal pathologies}},
year=2001,
booktitle={Proc. Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA 2001)},
pages={156--162}
}