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Memorias de investigación
Communications at congresses:
Use of Acoustic landmarks and GMM-UBM blend in the automatic detection of Parkinson's disease
Year:2017
Research Areas
  • Information technology and adata processing
Information
Abstract
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.
International
Si
Congress
10th International Workshop Models and Analysis of Vocal Emissions for Biomedical Applications
960
Place
Reviewers
Si
ISBN/ISSN
978-88-6453-607-1
Start Date
13/12/2017
End Date
15/12/2017
From page
73
To page
76
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)
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