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Parkinson’s Disease Detection from Speech Using Convolutional Neural Networks
Kaunas University of Technology, Kaunas, Lithuania.ORCID iD: 0000-0002-4769-4527
Kaunas University of Technology, Kaunas, Lithuania.ORCID iD: 0000-0002-0415-1434
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Kaunas University of Technology, Kaunas, Lithuania.ORCID iD: 0000-0003-2185-8973
Kaunas University of Technology, Kaunas, Lithuania.
2018 (English)In: Smart objects and technologies for social good: Third International Conference, GOODTECHS 2017, Pisa, Italy, November 29-30, 2017, Proceedings / [ed] Guidi, B., Ricci, L., Calafate, C., Gaggi, O., Marquez-Barja, J., Cham: Springer, 2018, Vol. 233, p. 206-215Conference paper, Published paper (Refereed)
Abstract [en]

Application of deep learning tends to outperform hand-crafted features in many domains. This study uses convolutional neural networks to explore effectiveness of various segments of a speech signal,? – text-dependent pronunciation of a short sentence, – in Parkinson’s disease detection task. Besides the common Mel-frequency spectrogram and its first and second derivatives, inclusion of various other input feature maps is also considered. Image interpolation is investigated as a solution to obtain a spectrogram of fixed length. The equal error rate (EER) for sentence segments varied from 20.3% to 29.5%. Fusion of decisions from sentence segments achieved EER of 14.1%, whereas the best result when using the full sentence exhibited EER of 16.8%. Therefore, splitting speech into segments could be recommended for Parkinson’s disease detection. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.

Place, publisher, year, edition, pages
Cham: Springer, 2018. Vol. 233, p. 206-215
Series
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, E-ISSN 1867-8211 ; 233
Keywords [en]
Parkinson’s disease, Audio signal processing, Convolutional neural network, Information fusion
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-36617DOI: 10.1007/978-3-319-76111-4_21Libris ID: 22545990ISBN: 978-3-319-76111-4 (electronic)OAI: oai:DiVA.org:hh-36617DiVA, id: diva2:1198161
Conference
Third EAI International Conference on Smart Objects and Technologies for Social Good, GOODTECHS 2017, Pisa, Italy, November 29-30, 2017
Note

Funding: Research Council of Lithuania (No. MIP-075/2015)

Available from: 2018-04-16 Created: 2018-04-16 Last updated: 2018-04-17Bibliographically approved

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Verikas, Antanas

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