Fig 1. Figure describing the taxonomy of SMD according to the Darley, Aronson, and Brown model.

Note that the taxonomy panel was produced by [10] and modified in this paper. Acoustic features representing the vocal tract and capturing formant structure are amongst the most discriminant in ASR tasks. Our interest is to detect the presence or absence of Parkinson’s through such acoustic features. Hence, since one of the early symptoms of Parkinson’s is ataxic speech, which implies several speech abnormalities in the vocal tract, this will be the set of anomalies we aim to discriminate. Furthermore, based on [17], our goal is to construct an ASR-SD system able to deal with complex settings such as non-stationarity of the speech, small sample sizes, unbalanced data, and interpretation of the obtained results concerning gender voices, carrying different formant structure.