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

Zlotnik, Alexander; Montero Martínez, Juan Manuel; San Segundo Hernández, Rubén; Gallardo Antolín, Ascensión

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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

Publisher: International Speech Communication Association (ISCA)

Issued date: 2015

Citation: INTERSPEECH 2015: 16th Annual Conference of the International Speech Communication Association, Dresden, Germany, September 6-10, 2015. ISCA, 2015, Pp. 503-507

xmlui.dri2xhtml.METS-1.0.item-contributor-funder: European Commission
Ministerio de Economía y Competitividad (España)

Sponsor: The work leading to these results has been partly supported by Spanish Government grants TEC2014-53390-P and DPI2014-53525-C3-2-R, and from the European Union under grant agreement number 287678 (SIMPLE4ALL). Authors also thank all the other members of the Speech Technology Group at UPM and Grupo de Procesado Multimedia at UC3M for the continuous and fruitful discussion on these topics.

Publisher version: https://www.isca-speech.org/archive/interspeech_2015/i15_0503.html

Project: Gobierno de España. TEC2014-53390-P
Gobierno de España. DPI2014-53525-C3-2-R
info:eu-repo/grantAgreement/EC/FP7/287678-SIMPLE4ALL

Keywords: Random forest , Regression , Parkinson's disease , ASR features , Intelligibility

URI: http://hdl.handle.net/10016/31990

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 [+]

Description:

Proceeding of: 16th Annual Conference of the International Speech Communication Association (INTERSPEECH 2015), Dresden, Germany, September 6-10, 2015

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