Ing. Zoltán Galáž, Ing. Jiří Mekyska, prof. Ing. Zdeněk Smékal, CSc.
Date of creation: 8. 10. 2016
It is possible to download software here.
Publication to be cited
MEKYSKA, J.; GALÁŽ, Z.; MŽOUREK, Z.; SMÉKAL, Z.; REKTOROVÁ, I.; ELIÁŠOVÁ, I.; KOŠŤÁLOVÁ, M.; MRAČKOVÁ, M.; BERANKOVA, D.; FAÚNDEZ ZANUY, M.; LOPEZ-DE-IPINA, K.; ALONSO-HERNANDEZ, J. Assessing progress of Parkinson’ s disease using acoustic analysis of phonation. In 2015 4th International Work Conference on Bioinspired Intelligence (IWOBI). 2015. s. 111-118. ISBN: 978-1-4673-7845- 1.
GALÁŽ, Z.; MEKYSKA, J.; MŽOUREK, Z.; KISKA, T.; SMÉKAL, Z.; REKTOROVÁ, I. Degree of Parkinson’ s Disease Severity Estimation Based on Speech Signal Processing. In Proceedings of the 39th International Conference on Telecommunication and Signal Processing, TSP 2016. 1. 2016. s. 1-4. ISBN: 978-1-5090-1287- 9.
Phonation of vowels is the most commonly used speech task to analyse the vocal tract functionality. Using acoustic analysis, it is possible to identify instability and asynchronous behaviour of the vocal folds, vocal tremor, etc. These voice flaws are frequent in several in many disorders such as Parkinson’s disease, throat cancer, polyps, nodules, etc.
Vocal analysis tool (VAT) is programmed in the MATLAB programming environment. It provides a graphic user interface to compute and analyse several world-renowned conventional speech features characterizing vocal tract impairment. It also enables visualization of short-time energy and fundamental frequency evolution in time. The speech features:
- Maximum phonation time
- Standard deviation of fundamental frequency
- Harmonic-to-Noise ratio
Furthermore, VAT is implemented to analyse and compare voice recordings. During the analysis, it compares the mean value of the speech features computed for the previous recordings and the actual one using a radar graph approach. The demo file with several recordings are also provided to easily test the tool.
This work was supported by projects AZV 16-30805A, LO1401, COST IC1206 a 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.