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@inproceedings{1412788,
author = {Mucha, J. and Galaz, Z. and Mekyska, J. and Kiska, T. and Zvoncak, V. and Smekal, Z. and Eliášová, Ilona and Mračková, Martina and Košťálová, Milena and Rektorová, Irena and FaundezandZanuy, M. and AlonsoandHernandez, JB.},
address = {Barcelona},
booktitle = {40th International Conference on Telecommunications and Signal Processing, TSP 2017},
doi = {http://dx.doi.org/10.1109/TSP.2017.8076086},
editor = {Herencsar N.},
keywords = {acoustic analysis; binary classification; hypokinetic dysarthria; Parkinson’s disease; poem recitation},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Barcelona},
isbn = {978-1-5090-3982-1},
pages = {739-742},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
title = {Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation},
year = {2017}
}
TY - JOUR
ID - 1412788
AU - 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.
PY - 2017
TI - Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation
PB - Institute of Electrical and Electronics Engineers Inc.
CY - Barcelona
SN - 9781509039821
KW - acoustic analysis
KW - binary classification
KW - hypokinetic dysarthria
KW - Parkinson’s disease
KW - poem recitation
N2 - 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.
ER -
MUCHA, J., Z. GALAZ, J. MEKYSKA, T. KISKA, V. ZVONCAK, Z. SMEKAL, Ilona ELIÁŠOVÁ, Martina MRAČKOVÁ, Milena KOŠŤÁLOVÁ, Irena REKTOROVÁ, M. FAUNDEZ-ZANUY a JB. ALONSO-HERNANDEZ. Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation. Online. In Herencsar N. \textit{40th International Conference on Telecommunications and Signal Processing, TSP 2017}. Barcelona: Institute of Electrical and Electronics Engineers Inc., 2017, s.~739-742. ISBN~978-1-5090-3982-1. Dostupné z: https://dx.doi.org/10.1109/TSP.2017.8076086.
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