• DocumentCode
    1346326
  • Title

    Acoustical properties of speech as indicators of depression and suicidal risk

  • Author

    France, Daniel J. ; Shiavi, Richard G. ; Silverman, Stephen ; Silverman, Marilyn ; Wilkes, D. Mitchell

  • Author_Institution
    L-3 Commun., Salt Lake City, UT, USA
  • Volume
    47
  • Issue
    7
  • fYear
    2000
  • fDate
    7/1/2000 12:00:00 AM
  • Firstpage
    829
  • Lastpage
    837
  • Abstract
    Acoustic properties of speech have previously been identified as possible cues to depression, and there is evidence that certain vocal parameters may be used further to objectively discriminate between depressed and suicidal speech. Studies were performed to analyze and compare the speech acoustics of separate male and female samples comprised of normal individuals and individuals carrying diagnoses of depression and high-risk, near-term suicidality. The female sample consisted of ten control subjects, 17 dysthymic patients, and 21 major depressed patients. The male sample contained 24 control subjects, 21 major depressed patients, and 22 high-risk suicidal patients. Acoustic analyses of voice fundamental frequency (F 0), amplitude modulation (AM), formants, and power distribution were performed on speech samples extracted from audio recordings collected from the sample members. Multivariate feature and discriminant analyses were performed on feature vectors representing the members of the control and disordered classes. Features derived from the formant and power spectral density measurements were found to be the best discriminators of class membership in both the male and female studies. AM features emerged as strong class discriminators of the male classes. Features describing F 0 were generally ineffective discriminators in both studies. The results support theories that identify psychomotor disturbances as central elements in depression and suicidality.
  • Keywords
    amplitude modulation; medical signal processing; psychology; speech processing; audio recordings; depression indicator; discriminant analysis; dysthymic patients; female sample; formants; high-risk suicidal patients; major depressed patients; male sample; multivariate analysis; normal individuals; power distribution; speech acoustical properties; speech samples; suicidal risk indicator; vocal parameters; voice fundamental frequency; Acoustics; Amplitude modulation; Biomedical engineering; Biomedical monitoring; Frequency; Performance analysis; Power distribution; Psychiatry; Psychology; Speech analysis; Adult; Biomedical Engineering; Case-Control Studies; Depression; Female; Humans; Male; Middle Aged; Risk Factors; Speech Acoustics; Suicide;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.846676
  • Filename
    846676