The proposed method achieved average classification accuracies of up to 92 % in vowels, and 97 % in words. There is an improvement in accuracy ranging from 10% to 40 % compared to existing methods. Further, the developed models are evaluated upon an independent dataset. Results on this separate test set show accuracies ranging from 63% to 75% in vowels, and from 53% to 75% in isolated words. Regarding the dysarthria level evaluation, Spearman’s correlations between original and predicted labels are around 0.81 in sustained vowels and in isolated words. The results indicate that the proposed approach is suitable and robust for the automatic detection of PD. CLICK TO REVIEW