Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation

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Publikace nespadá pod Pedagogickou fakultu, ale pod Středoevropský technologický institut. Oficiální stránka publikace je na webu muni.cz.
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MUCHA J. GALAZ Z. MEKYSKA J. KISKA T. ZVONCAK V. SMEKAL Z. ELIÁŠOVÁ Ilona MRAČKOVÁ Martina KOŠŤÁLOVÁ Milena REKTOROVÁ Irena FAUNDEZ-ZANUY M. ALONSO-HERNANDEZ JB.

Rok publikování 2017
Druh Článek ve sborníku
Konference 40th International Conference on Telecommunications and Signal Processing, TSP 2017
Fakulta / Pracoviště MU

Středoevropský technologický institut

Citace
Doi http://dx.doi.org/10.1109/TSP.2017.8076086
Klíčová slova acoustic analysis; binary classification; hypokinetic dysarthria; Parkinson’s disease; poem recitation
Popis Up to 90% of patients with Parkinson’s disease (PD) suffer from hypokinetic dysarthria (HD). In this work, we analysed the power of conventional speech features quantifying imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy speech. For this purpose, 152 speakers (53 healthy speakers, 99 PD patients) were examined. Only mildly strong correlation between speech features and clinical status of the speakers was observed. In case of univariate classification analysis, sensitivity of 62.63% (imprecise articulation), 61.62% (dysprosody), 71.72% (speech dysfluency) and 59.60% (speech quality deterioration) was achieved. Multivariate classification analysis improved the classification performance. Sensitivity of 83.42% using only two features describing imprecise articulation and speech quality deterioration in HD was achieved. We showed the promising potential of the selected speech features and especially the use of poem recitation task to quantify and identify HD in PD.
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