Random forest-based prediction of Parkinson's disease progression using acoustic, ASR and intelligibility features

Zlotnik, Alexander and Montero Martínez, Juan Manuel and San Segundo Hernández, Rubén and Gallardo Antolín, Ascensión (2015). Random forest-based prediction of Parkinson's disease progression using acoustic, ASR and intelligibility features. In: "16th Annual Conference of the International Speech Communication Association (INTERSPEECH 2015)", 06/09/2015 - 10/09/2015, Dresden, Germany. pp. 503-507.

Description

Title: Random forest-based prediction of Parkinson's disease progression using acoustic, ASR and intelligibility features
Author/s:
  • Zlotnik, Alexander
  • Montero Martínez, Juan Manuel
  • San Segundo Hernández, Rubén
  • Gallardo Antolín, Ascensión
Item Type: Presentation at Congress or Conference (Article)
Event Title: 16th Annual Conference of the International Speech Communication Association (INTERSPEECH 2015)
Event Dates: 06/09/2015 - 10/09/2015
Event Location: Dresden, Germany
Title of Book: 16th Annual Conference of the International Speech Communication Association (INTERSPEECH 2015)
Date: 2015
Subjects:
Freetext Keywords: Random forest, regression, Parkinson’s disease, ASR features, intelligibility
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The Interspeech ComParE 2015 PC Sub-Challenge consists of automatically determining the degree of Parkinson?s condition using exclusively the patient?s voice. In this paper, we face this problem as a regression task and in order to succeed, we propose the use of an ensemble learning method, Random Forest (RF), in combination with features of different nature: acoustic characteristics, features derived from the output of an Automatic Speech Recognition system (ASR) and non-intrusive intelligibility measures. The system outperforms the baseline results achieving a relative improvement higher than 19% in the development set.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2014-53390-PUnspecifiedUnspecifiedUnspecified
Government of SpainDPI2014-53525-C3-2-RUnspecifiedUnspecifiedUnspecified
FP728767SIMPLE4ALLUnspecifiedUnspecified

More information

Item ID: 42002
DC Identifier: http://oa.upm.es/42002/
OAI Identifier: oai:oa.upm.es:42002
Deposited by: Memoria Investigacion
Deposited on: 03 Sep 2016 10:14
Last Modified: 03 Sep 2016 10:14
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