• DocumentCode
    1374764
  • Title

    Detection of Clinical Depression in Adolescents’ Speech During Family Interactions

  • Author

    Low, Lu-Shih Alex ; Maddage, Namunu C. ; Lech, Margaret ; Sheeber, Lisa B. ; Allen, Nicholas B.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., R. Melbourne Inst. of Technol., Melbourne, VIC, Australia
  • Volume
    58
  • Issue
    3
  • fYear
    2011
  • fDate
    3/1/2011 12:00:00 AM
  • Firstpage
    574
  • Lastpage
    586
  • Abstract
    The properties of acoustic speech have previously been investigated as possible cues for depression in adults. However, these studies were restricted to small populations of patients and the speech recordings were made during patients´ clinical interviews or fixed-text reading sessions. Symptoms of depression often first appear during adolescence at a time when the voice is changing, in both males and females, suggesting that specific studies of these phenomena in adolescent populations are warranted. This study investigated acoustic correlates of depression in a large sample of 139 adolescents (68 clinically depressed and 71 controls). Speech recordings were made during naturalistic interactions between adolescents and their parents. Prosodic, cepstral, spectral, and glottal features, as well as features derived from the Teager energy operator (TEO), were tested within a binary classification framework. Strong gender differences in classification accuracy were observed. The TEO-based features clearly outperformed all other features and feature combinations, providing classification accuracy ranging between 81%-87% for males and 72%-79% for females. Close, but slightly less accurate, results were obtained by combining glottal features with prosodic and spectral features (67%-69% for males and 70%-75% for females). These findings indicate the importance of nonlinear mechanisms associated with the glottal flow formation as cues for clinical depression.
  • Keywords
    medical disorders; medical signal processing; patient diagnosis; signal classification; speech; speech processing; Teager energy operator; adolescence; cepstral feature; clinical depression detection; family interactions; fixed-text reading session; glottal feature; glottal flow formation; patient clinical interviews; prosodic feature; signal classification; spectral feature; speech recordings; Acoustics; Correlation; Feature extraction; Frequency measurement; Harmonic analysis; Speech; Timing; Acoustic features; adolescents; clinical depression classification; naturalistic speech; Adolescent; Adolescent Psychology; Depression; Diagnosis, Computer-Assisted; Family Relations; Female; Humans; Male; Pattern Recognition, Automated; Speech; Speech Acoustics;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2010.2091640
  • Filename
    5629355