2017
Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation
MUCHA, J.; Z. GALAZ; J. MEKYSKA; T. KISKA; V. ZVONCAK et al.Základní údaje
Originální název
Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation
Autoři
MUCHA, J.; Z. GALAZ; J. MEKYSKA; T. KISKA; V. ZVONCAK; Z. SMEKAL; Ilona ELIÁŠOVÁ; Martina MRAČKOVÁ; Milena KOŠŤÁLOVÁ ORCID; Irena REKTOROVÁ; M. FAUNDEZ-ZANUY a JB. ALONSO-HERNANDEZ
Vydání
Barcelona, 40th International Conference on Telecommunications and Signal Processing, TSP 2017, od s. 739-742, 4 s. 2017
Nakladatel
Institute of Electrical and Electronics Engineers Inc.
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
30103 Neurosciences
Stát vydavatele
Španělsko
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
elektronická verze "online"
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14740/17:00095717
Organizační jednotka
Středoevropský technologický institut
ISBN
978-1-5090-3982-1
UT WoS
EID Scopus
Klíčová slova anglicky
acoustic analysis; binary classification; hypokinetic dysarthria; Parkinson’s disease; poem recitation
Štítky
Změněno: 24. 4. 2020 12:34, Mgr. Pavla Foltynová, Ph.D.
Anotace
V originále
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.
Návaznosti
| NV16-30805A, projekt VaV |
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