ausblenden:
Schlagwörter:
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MPIPKS:
Stochastic processes
Zusammenfassung:
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
perform 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 coming from healthy people and from patients affected by
T1A glottis cancer, one is able to understand which kind of interventions are 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.
