Assessing Parkinson's disease from speech using fisher vectors

Egas López JV, Orozco Arroyave JR, Gosztolya G (2019)

Publication Type: Conference contribution

Publication year: 2019

Publisher: International Speech Communication Association

Book Volume: 2019-September

Pages Range: 3063-3067

Conference Proceedings Title: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Event location: Graz AT

DOI: 10.21437/Interspeech.2019-2217

Abstract

Parkinson's Disease (PD) is a neuro-degenerative disorder that affects primarily the motor system of the body. Besides other functions, the subject's speech also deteriorates during the disease, which allows for a non-invasive way of automatic screening. In this study, we represent the utterances of subjects having PD and those of healthy controls by means of the Fisher Vector approach. This technique is very common in the area of image recognition, where it provides a representation of the local image descriptors via frequency and high order statistics. In the present work, we used four frame-level feature sets as the input of the FV method, and applied (linear) Support Vector Machines (SVM) for classifying the speech of subjects. We found that our approach offers superior performance compared to classification based on the i-vector and cosine distance approach, and it also provides an efficient combination of machine learning models trained on different feature sets or on different speaker tasks.

Authors with CRIS profile

Juan Rafael Orozco Arroyave Professur für Informatik (Mustererkennung)

Involved external institutions

University of Szeged / József Attila Tudományegyetem Szeged HU Hungary (HU)

How to cite

APA:

Egas López, J.V., Orozco Arroyave, J.R., & Gosztolya, G. (2019). Assessing Parkinson's disease from speech using fisher vectors. In Gernot Kubin, Thomas Hain, Bjorn Schuller, Dina El Zarka, Petra Hodl (Eds.), Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH (pp. 3063-3067). Graz, AT: International Speech Communication Association.

MLA:

Egas López, José Vicente, Juan Rafael Orozco Arroyave, and Gábor Gosztolya. "Assessing Parkinson's disease from speech using fisher vectors." Proceedings of the 20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019, Graz Ed. Gernot Kubin, Thomas Hain, Bjorn Schuller, Dina El Zarka, Petra Hodl, International Speech Communication Association, 2019. 3063-3067.

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