Descripción
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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. | |
Internacional
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Si |
Nombre congreso
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INTERSPEECH 2015 16th Annual Conference of the International Speech Communication Association |
Tipo de participación
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960 |
Lugar del congreso
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Dresden, Germany |
Revisores
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Si |
ISBN o ISSN
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978-1-5108-1790-6 |
DOI
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Fecha inicio congreso
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06/09/2015 |
Fecha fin congreso
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10/09/2015 |
Desde la página
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503 |
Hasta la página
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507 |
Título de las actas
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Proceedings of 16TH Annual Conference of the international speech communication association |