Ing. Zoltán Galáž, Ing. Jiří Mekyska, prof. Ing. Zdeněk Smékal, CSc.
Date of creation: 2. 6. 2016
It is possible to download software here.
Publication to be cited
GALÁŽ, Z.; MEKYSKA, J.; MŽOUREK, Z.; SMÉKAL, Z.; REKTOROVÁ, I.; ELIÁŠOVÁ, I.; KOŠŤÁLOVÁ, M.; MRAČKOVÁ, M.; BERANKOVA, D. Prosodic analysis of neutral, stress-modified and rhymed speech in patients with Parkinson’ s disease. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2016, č. 1, s. 1-17. ISSN: 0169- 2607.
GALÁŽ, Z. Quantification of Prosodic Impairment in Patients with Idiopathic Parkinson’s Disease. In Proceedings of the 22nd Conference STUDENT EEICT 2016. Brno: 2016. s. 538-542. ISBN: 978-80-214-5350- 0.
GALÁŽ, Z. Potential of Prosodic Features to Estimate Degree of Parkinson’s Disease Severity. In Proceedings of the 22nd Conference STUDENT EEICT 2016. Brno: 2016. s. 533-537. ISBN: 978-80-214-5350- 0.
Objective analysis of Parkinson’s disease (PD) based on quantification of hypokinetic dysarthria (HD) is a modern and prospective method of diagnosis, assessment, monitoring and treating of the disease. It has been shown that approximately 60 – 90% of patients with PD suffer from HD. HD is characterized by impaired respiration, phonation, articulation, prosody and speech fluency. Objective quantification of the previously mentioned speech flaws in HD can provide valuable information about the underlying mechanism of HD and also PD, which can often be hidden above the human’s perception and therefore can barely be identified by a subjective examination at the clinic.
Dysarthric speech quantification tool is an open-source library comprising a variety of speech features conventionally used in the field of acoustic analysis of dysarthric speech. It is programmed in the Python programming language and it built on modern, standard libraries such as NumPy, SciPy, or Matplotlib, see https://www.scipy.org/. This tool also provides functions to handle the speech recordings (loading, saving, etc.), perform a speech signal pre-processing (peek finding, interpolation, segmentation, etc.), and also classes to represent speech signals and the patients with HD in PD. This tool provide a quick, easy-to-use, objective quantification of speech flaws associated with the presence of HD.
This work was supported by projects AZV 16-30805A, LO1401, COST IC1206 and FEKT-S-14-2335. The described research was performed in laboratories supported by the SIX project; the registration number CZ.1.05/2.1.00/03.0072, the operational program Research and Development for Innovation.