Medical Engineering & Physics
Volume 32, Issue 9 , Pages 1074-1079, November 2010

Acoustic and temporal analysis of speech: A potential biomarker for schizophrenia

  • Viliam Rapcan

      Affiliations

    • Trinity Centre for Bioengineering, Trinity College Dublin, Dublin 2, Ireland
    • Corresponding Author InformationCorresponding author. Tel.: +353 18964214; fax: +353 16795554.
  • ,
  • Shona D’Arcy

      Affiliations

    • Trinity Centre for Bioengineering, Trinity College Dublin, Dublin 2, Ireland
  • ,
  • Sherlyn Yeap

      Affiliations

    • Our Lady's Hospital, Navan, Ireland
  • ,
  • Natasha Afzal

      Affiliations

    • Fraser Health Care, Vancouver, Canada
  • ,
  • Jogin Thakore

      Affiliations

    • The Cognitive Neurophysiology Laboratory, St. Vincent's Hospital, Fairview, Dublin, Ireland
  • ,
  • Richard B. Reilly

      Affiliations

    • Trinity Centre for Bioengineering, Trinity College Dublin, Dublin 2, Ireland
    • The Cognitive Neurophysiology Laboratory, St. Vincent's Hospital, Fairview, Dublin, Ireland
    • Trinity Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland

Received 31 March 2010; received in revised form 19 July 2010; accepted 20 July 2010. published online 09 August 2010.

Abstract 

Currently, there are no established objective biomarkers for the diagnosis or monitoring of schizophrenia. It has been previously reported that there are notable qualitative differences in the speech of schizophrenics. The objective of this study was to determine whether a quantitative acoustic and temporal analysis of speech may be a potential biomarker for schizophrenia.

In this study, 39 schizophrenic patients and 18 controls were digitally recorded reading aloud an emotionally neutral text passage from a children's story. Temporal, energy and vocal pitch features were automatically extracted from the recordings. A classifier based on linear discriminant analysis was employed to differentiate between controls and schizophrenic subjects.

Processing the recordings with the algorithm developed demonstrated that it is possible to differentiate schizophrenic patients and controls with a classification accuracy of 79.4% (specificity=83.6%, sensitivity=75.2%) based on speech pause related parameters extracted from recordings carried out in standard office (non-studio) environments.

Acoustic and temporal analysis of speech may represent a potential tool for the objective analysis in schizophrenia.

Keywords: Acoustic and temporal analysis, Speech, Schizophrenia, Biomarker, Vocal pitch, Energy, Pause, Utterance

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PII: S1350-4533(10)00165-7

doi:10.1016/j.medengphy.2010.07.013

Medical Engineering & Physics
Volume 32, Issue 9 , Pages 1074-1079, November 2010