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Speech and Sound Use in a Remote Monitoring System for Health Care

  • Michel Vacher
  • Jean-François Serignat
  • Stéphane Chaillol
  • Dan Istrate
  • Vladimir Popescu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4188)

Abstract

Ageing affects the economic and social foundations of societies at world level. Health care has to respond to the challenge that population ageing presents. Medical remote monitoring needs human operator to be assisted by means of smart information systems. Physiological and position sensors give numerous data, but speech analysis and sound classification can give interesting additional information about the patient and may help in decision-making. The entire analysis system is composed of parallel tasks: signal detection and channel selection, sound/speech classification, life sound classification and speech recognition. The multichannel sound processing allows us to localize the source of sound in the apartment and to select appropriate signal segments for analysis. Recognized key words indicative of a distress situation are extracted from sentences. Key words and classification results are sent to the medical remote monitoring application through network. An adapted speech corpus was recorded in French and used for evaluation purposes.

Keywords

Hide Markov Model Speech Recognition Gaussian Mixture Model Gaussian Model Remote Monitoring 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Michel Vacher
    • 1
  • Jean-François Serignat
    • 1
  • Stéphane Chaillol
    • 1
  • Dan Istrate
    • 1
  • Vladimir Popescu
    • 1
  1. 1.CLIPS-IMAG, UMR CNRS-UJF-INPG 5524GrenobleFrance

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