14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Automatic Evaluation of Parkinson's Speech — Acoustic, Prosodic and Voice Related Cues

Tobias Bocklet (1), Stefan Steidl (1), Elmar Nöth (1), Sabine Skodda (2)

(1) FAU Erlangen-Nürnberg, Germany
(2) Knappschaftskrankenhaus Bochum, Germany

Articulation and phonation is affected in 70% to 90% of patients with Parkinson's disease (PD). This study focuses on the question whether speech carries information about 1. PD being present at a speaker or not, and 2. estimating the severity of PD (if present). We first perform classification experiments focusing on the automatic detection of PD as a 2-class problem (PD vs. healthy speakers). The detection of severity is described as a 3-class task based on the Unified Parkinson's Disease Rating Scale (UPDRS) ratings. We employ acoustic, prosodic and glottal features on different kinds of speech tests: various syllable repetition tasks, read sentences and texts, and monologues. Classification is performed in either case by SVMs. We report recognition results of 81.9% when trying to differentiate between normally speaking persons and speakers with PD. With system fusion we achieved a recognition results of 59.1% on the task of UPDRS classification.

Full Paper

Bibliographic reference.  Bocklet, Tobias / Steidl, Stefan / Nöth, Elmar / Skodda, Sabine (2013): "Automatic evaluation of parkinson's speech — acoustic, prosodic and voice related cues", In INTERSPEECH-2013, 1149-1153.