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Abstract:
We discuss how vocal disorders can be post-corrected via a simple nonlinear noise reduction scheme, This work is motivated by the need of a better understanding of voice dysfunctions. This would entail a 2-fold advantage for affected patients: Physicians can perforin better surgical interventions and on the other hand researchers can try to build up devices that can help to improve voice quality. i.e. in a phone conversation, avoiding any surgical treatment. As a first step. a proper signal classification is performed, through the idea of geometric signal separation in a feature space, Then through the analysis of the different regions populated by the samples coining from healthy people and from patients affected by TIA glottis cancer, one is able to understand which kind of interventions Lire necessary in order to correct the illness, i.e. to move the corresponding feature vector from the sick region to the healthy one. We discuss such a filter and show its performance. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.
