Publication detail

Preliminary Acoustic Analysis of Noise Components in Patients In Parkinsons Disease

GALÁŽ, Z.

Original Title

Preliminary Acoustic Analysis of Noise Components in Patients In Parkinsons Disease

English Title

Preliminary Acoustic Analysis of Noise Components in Patients In Parkinsons Disease

Type

conference paper

Language

en

Original Abstract

This paper deals with acoustic analysis of noise components extracted from speech signals of patients with Parkinsons disease (PD) who recited a poem. Experimental dataset consisted of 97 PD patients with different disease progress and 55 healthy controls (HC). The analysis is based on parametrization of 2 rhymes recitation using dysphonia features. We obtained classification accuracy 76.66% for female speakers, 69.65% for male speakers and 69.24% for the mixture of both genders

English abstract

This paper deals with acoustic analysis of noise components extracted from speech signals of patients with Parkinsons disease (PD) who recited a poem. Experimental dataset consisted of 97 PD patients with different disease progress and 55 healthy controls (HC). The analysis is based on parametrization of 2 rhymes recitation using dysphonia features. We obtained classification accuracy 76.66% for female speakers, 69.65% for male speakers and 69.24% for the mixture of both genders

Keywords

Parkinsons disease, Empirical Mode Decomposition, hypokinetic dysarthria, dysphonia

RIV year

2015

Released

23.04.2015

Location

Brno

ISBN

978-80-214-5148-3

Book

Proceedings of the 21st Conference STUDENT EEICT 2015

Pages from

476

Pages to

480

Pages count

5

BibTex


@inproceedings{BUT114620,
  author="Zoltán {Galáž}",
  title="Preliminary Acoustic Analysis of Noise Components in Patients In Parkinsons Disease",
  annote="This paper deals with acoustic analysis of noise components extracted from speech signals of patients with Parkinsons disease (PD) who recited a poem. Experimental dataset consisted of 97
PD patients with different disease progress and 55 healthy controls (HC). The analysis is based on
parametrization of 2 rhymes recitation using dysphonia features. We obtained classification accuracy 76.66% for female speakers, 69.65% for male speakers and 69.24% for the mixture of both genders",
  booktitle="Proceedings of the 21st Conference STUDENT EEICT 2015",
  chapter="114620",
  howpublished="electronic, physical medium",
  year="2015",
  month="april",
  pages="476--480",
  type="conference paper"
}