Study of the automatic detection of Parkison's Disease based on speaker recognition technologies and allophonic distillation

Abstract

The use of new tools to detect Parkinson´s Disease (PD) from speech articulatory movements can have a considerable impact in the diagnosis of patients. In this study, a novel approach involving speaker recognition techniques with allophonic distillation is proposed and tested separately in four parkinsonian speech databases (205 patients and 186 controls in total). The results of applying this new scheme in the databases provides up to 94% of accuracy in the automatic detection of PD and improvements up to 9% respect to baseline techniques. Results not only point towards the importance of the segmentation of the speech for the differentiation of parkinsonian and control speakers but confirm previous findings about the relevance of plosives and fricatives in the detection of parkinsonian dysarthria.