Phonation and Articulation Analysis of Spanish Vowels for Automatic Detection of Parkinson’s Disease

  • Juan Rafael Orozco-Arroyave
  • Elkyn Alexander Belalcázar-Bolaños
  • Julián David Arias-Londoño
  • Jesús Francisco Vargas-Bonilla
  • Tino Haderlein
  • Elmar Nöth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8655)


Parkinson’s disease (PD) is a chronic neurodegenerative disorder of the nervous central system and it can affect the communication skills of the patients. There is an interest in the research community to develop computer aided tools for the analysis of the speech of people with PD for detection and monitoring.

In this paper, three new acoustic measures for the simultaneous analysis of the phonation and articulation of patients with PD are presented. These new measures along with other classical articulation and perturbation features are objectively evaluated with a discriminant criterion. According to the results, the speech of people with PD can be detected with an accuracy of 81% when phonation and articulation features are combined.


Parkinson’s disease phonation articulation acoustics nonlinear dynamics 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    de Rijk, M., et al.: Prevalence of Parkinson’s Disease in Europe: A collaborative study of population-based cohorts. Neurology 54, 21–23 (2000)Google Scholar
  2. 2.
    Ramig, L., Fox, C., Sapir, S.: Speech Treatment for Parkinson’s Disease. Expert Review Neurotherapeutics 8(2), 297–309 (2008)CrossRefGoogle Scholar
  3. 3.
    Darley, F., Aronson, A., Brown, J.: Differential Diagnosis Patterns of Dysarthria. Motor Speech Disorders (1975)Google Scholar
  4. 4.
    Little, M.A., McSharry, P., Hunter, E., Spielman, J., Ramig, L.: Suitability of Dysphonia Measurements for Telemonitoring of Parkinson’s Disease. IEEE Transactions on Bio-medical Engineering 56(4), 1015–1022 (2009)CrossRefGoogle Scholar
  5. 5.
    Bocklet, T., Nöth, E., Stemmer, G., Ruzickova, H., Rusz, J.: Detection of Persons with Parkinson’s Disease by Acoustic, Vocal and Prosodic Analysis. In: Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp. 478–483 (2011)Google Scholar
  6. 6.
    Bayestehtashk, A., Asgari, M., Shafran, I., Mcnames, J.: Fully Automated Assessment of the Severity of Parkinson’s Disease from Speech. Computer Speech & Language, 1–14 (to appear, 2014)Google Scholar
  7. 7.
    National Collaborating Centre for Chronic Conditions: Parkinson’s Disease: National Clinical Guideline for Diagnosis and Management in Primary and Secondary Care. Royal College of Physicians, London (2006)Google Scholar
  8. 8.
    Rusz, J., Cmejla, R., Ruzickova, H., Ruzicka, E.: Quantitative Acoustic Measurements for Characterization of Speech and Voice Disorders in Early Untreated Parkinson’s Disease. The Journal of the Acoustical Society of America 129(1), 350–367 (2011)CrossRefGoogle Scholar
  9. 9.
    Skodda, S., Visser, W., Schlegel, U.: Vowel Articulation in Parkinson’s Disease. Journal of Voice 25(4), 467–472 (2011)CrossRefGoogle Scholar
  10. 10.
    Stebbing, G., Goetz, C.: Factor Structure of the Unified Parkinson’s Disease Rating Scale: Motor Examination Section. Movement Disorders 13, 633–636 (1998)CrossRefGoogle Scholar
  11. 11.
    Hoehn, M.M., Yahr, M.D.: Parkinsonism: Onset, Progression, and Mortality. Neurology 17, 427–442 (1967)CrossRefGoogle Scholar
  12. 12.
    Orozco-Arroyave, J., Arias-Londoño, J., Vargas-Bonilla, J., González-Rátiva, M., Nöth, E.: New Spanish Speech Corpus Database for the Analysis of People Suffering from Parkinson’s Disease. In: Proceedings of the 9th Language Resources and Evaluation Conference, LREC (to appear, 2014)Google Scholar
  13. 13.
    Lee, V., Zhou, X., Rahn, D., Wang, E., Jiang, J.: Perturbation and Nonlinear Dynamic Analysis of Acoustic Phonatory Signal in Parkinsonian Patients Receiving Deep Brain Stimulation. Journal of Communication Disorders 41(6), 485–500 (2008)CrossRefGoogle Scholar
  14. 14.
    Jiang, J., Zhang, Y., McGilligan, C.: Chaos in Voice: From Modeling to Measurement. Journal of Voice 20(1), 2–17 (2006)CrossRefGoogle Scholar
  15. 15.
    Orozco-Arroyave, J.R., Vargas-Bonilla, J.F., Arias-Londoño, J.D., Murillo-Rendón, S., Castellanos-Domínguez, G., Garcés, J.: Nonlinear Dynamics for Hypernasality Detection in Spanish Vowels and Words. Cognitive Computation 5(4), 448–457 (2013)CrossRefGoogle Scholar
  16. 16.
    Schölkopf, B., Smola, A.: Learning With Kernel. The MIT Press (2002)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Juan Rafael Orozco-Arroyave
    • 1
    • 2
  • Elkyn Alexander Belalcázar-Bolaños
    • 1
  • Julián David Arias-Londoño
    • 1
  • Jesús Francisco Vargas-Bonilla
    • 1
  • Tino Haderlein
    • 2
  • Elmar Nöth
    • 2
    • 3
  1. 1.Universidad de AntioquiaMedellínColombia
  2. 2.Friedrich-Alexander-UniversitätErlangen-NürnbergGermany
  3. 3.King Abdulaziz UniversityJeddahSaudi Arabia

Personalised recommendations