Communications at congresses:
Use of Acoustic landmarks and GMM-UBM blend in the automatic detection of Parkinson's disease
Use of Acoustic landmarks and GMM-UBM blend in the automatic detection of Parkinson's disease
Year:2017
Research Areas
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Information technology and adata processing
Information
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Abstract
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| New tools based on speech analysis can improve and accelerate diagnosis of Parkinson's disease. In this work, the use of some specific segments of speech, around the so called Acoustic Landamarks, are used with different families of features such as acoustic cues or Rasta-PLP and GMM-UBM-Blend classification methods to detect Parkinson's disease. Results of 87% are obtained. Burst segmentes provide the most relevant information when detecting Parkinson's disease whjile GMM-UMB-Blend is revealed as a promising techinique when using small databases and segmented speech. | |
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International
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Congress
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10th International Workshop Models and Analysis of Vocal Emissions for Biomedical Applications |
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960 |
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Place
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Reviewers
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ISBN/ISSN
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978-88-6453-607-1 |
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Start Date
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13/12/2017 |
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End Date
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15/12/2017 |
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From page
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73 |
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To page
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76 |
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Models and Analysis of Vocal Emissions for Biomedical Applications: 10th Internation Workshop |
Participants
- Autor: Laureano Moro Velazquez (UPM)
- Autor: Jorge Andres Gomez Garcia (UPM)
- Autor: Juan Ignacio Godino Llorente (UPM)
- Autor: Jesús Villalba (John Hopkins University)
- Autor: Najim Dehak (John Hopkins University)
Research Group, Departaments and Institutes related
- Creador: Grupo de Investigación: Informática Aplicada al Procesado de Señal e Imagen
- Departamento: Teoría de la Señal y Comunicaciones (Provisional)
S2i 2021 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)