Design of a multimodal database for research on automatic detection of severe apnoea cases

Fernández Pozo, Rubén; Hernández Gómez, Luis Alfonso; Lopez Gonzalo, Eduardo; Alcazar, Jose; Portillo, Guillermo y Torre Toledano, Doroteo (2008). Design of a multimodal database for research on automatic detection of severe apnoea cases. En: "6th International conference on Language Resources and Evaluation, LREC 2008", 26/05/2008-01/06/2008, Marrakech, Marruecos. ISBN 2-9517408-4-0.

Descripción

Título: Design of a multimodal database for research on automatic detection of severe apnoea cases
Autor/es:
  • Fernández Pozo, Rubén
  • Hernández Gómez, Luis Alfonso
  • Lopez Gonzalo, Eduardo
  • Alcazar, Jose
  • Portillo, Guillermo
  • Torre Toledano, Doroteo
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 6th International conference on Language Resources and Evaluation, LREC 2008
Fechas del Evento: 26/05/2008-01/06/2008
Lugar del Evento: Marrakech, Marruecos
Título del Libro: CD-ROM Proceedings of the 6th International conference on Language Resources and Evaluation, LREC 2008
Fecha: 2008
ISBN: 2-9517408-4-0
Materias:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[img]
Vista Previa
PDF (Document Portable Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (160kB) | Vista Previa

Resumen

The aim of this paper is to present the design of a multimodal database suitable for research on new possibilities for automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases can be very useful to give priority to their early treatment optimizing the expensive and time-consuming tests of current diagnosis methods based on full overnight sleep in a hospital. This work is part of an on-going collaborative project between medical and signal processing groups towards the design of a multimodal database as an innovative resource to promote new research efforts on automatic OSA diagnosis through speech and image processing technologies. In this contribution we present the multimodal design criteria derived from the analysis of specific voice properties related to OSA physiological effects as well as from the morphological facial characteristics in apnoea patients. Details on the database structure and data collection methodology are also given as it is intended to be an open resource to promote further research in this field. Finally, preliminary experimental results on automatic OSA voice assessment are presented for the collected speech data in our OSA multimodal database. Standard GMM speaker recognition techniques obtain an overall correct classification rate of 82%. This represents an initial promising result underlining the interest of this research framework and opening further perspectives for improvement using more specific speech and image recognition technologies.

Más información

ID de Registro: 4309
Identificador DC: http://oa.upm.es/4309/
Identificador OAI: oai:oa.upm.es:4309
URL Oficial: http://www.lrec-conf.org/proceedings/lrec2008/summaries/454.html
Depositado por: Memoria Investigacion
Depositado el: 27 Sep 2010 09:21
Ultima Modificación: 20 Abr 2016 13:35
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • e-ciencia
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM