Study of the automatic detection of Parkison's Disease based on speaker recognition technologies and allophonic distillation

Moro Velázquez, Laureano and Gomez Garcia, Jorge Andres and Godino Llorente, Juan Ignacio and Rusz, Jan and Skodda, Sabine and Orozco-Arroyave, J. Rafael and Grandas, Francisco and Nöth, Elmar and Dehak, Najin (2018). Study of the automatic detection of Parkison's Disease based on speaker recognition technologies and allophonic distillation. In: "40th International Engineering in Medicine and Biology Society", 18/07/2020 - 21/07/2020, Honolulu, Hawai, USA. ISBN 978-1-5386-3646-6. pp. 1404-1407. https://doi.org/10.1109/EMBC.2018.8512562.

Description

Title: Study of the automatic detection of Parkison's Disease based on speaker recognition technologies and allophonic distillation
Author/s:
  • Moro Velázquez, Laureano
  • Gomez Garcia, Jorge Andres
  • Godino Llorente, Juan Ignacio
  • Rusz, Jan
  • Skodda, Sabine
  • Orozco-Arroyave, J. Rafael
  • Grandas, Francisco
  • Nöth, Elmar
  • Dehak, Najin
Item Type: Presentation at Congress or Conference (Article)
Event Title: 40th International Engineering in Medicine and Biology Society
Event Dates: 18/07/2020 - 21/07/2020
Event Location: Honolulu, Hawai, USA
Title of Book: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Date: 2018
ISBN: 978-1-5386-3646-6
Subjects:
Freetext Keywords: Voice pathology detection; Voice pathology identification; Gradient boosting; Gaussian mixture models; Random forest
Faculty: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Department: Ingeniería Audiovisual y Comunicaciones [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The use of new tools to detect Parkinson´s Disease (PD) from speech articulatory movements can have a considerable impact in the diagnosis of patients. In this study, a novel approach involving speaker recognition techniques with allophonic distillation is proposed and tested separately in four parkinsonian speech databases (205 patients and 186 controls in total). The results of applying this new scheme in the databases provides up to 94% of accuracy in the automatic detection of PD and improvements up to 9% respect to baseline techniques. Results not only point towards the importance of the segmentation of the speech for the differentiation of parkinsonian and control speakers but confirm previous findings about the relevance of plosives and fricatives in the detection of parkinsonian dysarthria.

More information

Item ID: 55198
DC Identifier: http://oa.upm.es/55198/
OAI Identifier: oai:oa.upm.es:55198
DOI: 10.1109/EMBC.2018.8512562
Official URL: https://embc.embs.org/2018/
Deposited by: Memoria Investigacion
Deposited on: 25 Feb 2020 14:35
Last Modified: 25 Feb 2020 14:35
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