Abstract
The progression of the disease in Parkinson’s patients is commonly evaluated with the unified Parkinson’s disease rating scale (UPDRS), which contains several items to assess motor and non–motor impairments. The patients develop speech impairments that can be assessed with a scale to evaluate dysarthria. Continuous monitoring of the patients is suitable to update the medication or the therapy. In this study, a robust speaker model based on the GMM–UBM approach is proposed for the continuous monitoring of the state of Parkinson’s patients. The model is trained with phonation, articulation, and prosody features with the aim of evaluating deficits on each speech dimension. The performance of the model is evaluated in two scenarios: the monitoring of the UPDRS score and the prediction of the dysarthria level of the speakers. The results indicate that the speaker models are suitable to track the disease progression, specially in terms of the evaluation of the dysarthia level of the speakers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hornykiewicz, O.: Biochemical aspects of Parkinson’s disease. Neurology 51(2 Suppl 2), S2–S9 (1998)
Goetz, C.G., et al.: Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov. Disord. 23(15), 2129–2170 (2008)
Rusz, J., Cmejla, R., Tykalova, T., Ruzickova, H., Klempir, J., Majerova, V., Picmausova, J., Roth, J., Ruzicka, E.: Imprecise vowel articulation as a potential early marker of Parkinson’s disease: effect of speaking task. J. Acoust. Soc. Am. 134(3), 2171–2181 (2013)
Enderby, P.M., Palmer, R.: FDA-2: Frenchay Dysarthria Assessment: Examiner’s Manual. Pro-Ed, Texas (2008)
Tsanas, A., Little, M., McSharry, P.E., Ramig, L.: Accurate telemonitoring of Parkinson’s disease progression by noninvasive speech tests. IEEE Trans. Biomed. Eng. 57(4), 884–893 (2010)
Skodda, S., Grönheit, W., Mancinelli, N., Schlegel, U.: Progression of voice and speech impairment in the course of Parkinson’s disease: a longitudinal study. Parkinson’s Dis. 2013, 1–8 (2013). Article ID 389195
Gómez-Vilda, P., Vicente-Torcal, M.C., Ferrández-Vicente, J.M., Álvarez-Marquina, A., Rodellar-Biarge, V., Nieto-Lluis, V., Martínez-Olalla, R.: Parkinson’s disease monitoring from phonation biomechanics. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Toledo-Moreo, F.J., Adeli, H. (eds.) IWINAC 2015. LNCS, vol. 9107, pp. 238–248. Springer, Cham (2015). doi:10.1007/978-3-319-18914-7_25
Arias-Vergara, T., Vásquez-Correa, J.C., Orozco-Arroyave, J.R., Vargas-Bonilla, J.F., Nöth, E.: Parkinson disease progression assessment from speech using GMM-UBM. In: Annual Conference of the International Speech Communication Association (INTERSPEECH), pp. 1933–1937 (2016)
Nöth, E., et al.: Remote monitoring of neurodegeneration through speech. In: Final Presentation of the Third Frederick Jelinek Memorial Summer Workshop (JSALT), August 2016
Vásquez-Correa, J.C., Orozco-Arroyave, J.R., Arora, R., Nöth, E., Dehak, N., Christensen, H., Rudzicz, F., Bocklet, T., Cernak, M., Chinaei, H., et al.: Multi-view representation learning via GCCA for multimodal analysis of Parkinson’s disease. In: 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017) (2017)
Orozco-Arroyave, J.R., Arias-Londoño, J.D., Vargas-Bonilla, J.F., Gonzalez-Rátiva, M.C., Nöth, E.: New Spanish speech corpus database for the analysis of people suffering from Parkinson’s disease. In: Language Resources and Evaluation Conference, (LREC), pp. 342–347 (2014)
Orozco-Arroyave, J.R., Vásquez-Correa, J.C., Hönig, F., Arias-Londoño, J.D., Vargas-Bonilla, J.F., Skodda, S., Rusz, J., Nöth, E.: Towards an automatic monitoring of the neurological state of the Parkinson’s patients from speech. In: 41st International Conference on Acoustic, Speech, and Signal Processing (ICASSP), pp. 6490–6494 (2016)
Orozco-Arroyave, J.R., Belalcazar-Bolaños, E.A., et al.: Characterization methods for the detection of multiple voice disorders: neurological, functional, and laryngeal diseases. IEEE J. Biomed. Health Inf. 19(6), 1820–1828 (2015)
Skodda, S., Visser, W., Schlegel, U.: Vowel articulation in parkinson’s disease. J. Voice 25(4), 467–472 (2011)
Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716–723 (1974)
You, C.H., Lee, K.A., Li, H.: GMM-SVM kernel with a Bhattacharyya-based distance for speaker recognition. IEEE Trans. Audio Speech Lang. Process. 18(6), 1300–1312 (2010)
Acknowledgments
The work reported here was started at JSALT 2016, and was supported by JHU via grants from DARPA (LORELEI), Microsoft, Amazon, Google and Facebook. Thanks also to CODI from University of Antioquia by the grant Numbers 2015–7683 and PRV16-2-01.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Vásquez-Correa, J.C., Castrillón, R., Arias-Vergara, T., Orozco-Arroyave, J.R., Nöth, E. (2017). Speaker Model to Monitor the Neurological State and the Dysarthria Level of Patients with Parkinson’s Disease. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-64206-2_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-64205-5
Online ISBN: 978-3-319-64206-2
eBook Packages: Computer ScienceComputer Science (R0)