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Cited by 256

The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.

Detection of Clinical Depression in Adolescents’ Speech During Family Interactions

Open access
Low, Lu-Shih Alex, Maddage, M C, Lech, M, Sheeber, L B, Allen, N B·2011·IEEE Transactions on Biomedical Engineering
DOI 10.1109/tbme.2010.2091640
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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.

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Metadata

Authors
Low, L.-S. A., Maddage, M. C., Lech, M., Sheeber, L. B., & Allen, N. B.
Venue
IEEE Transactions on Biomedical Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2011-03
Volume
58
Issue
3
Pages
574-586
ISSN
  • 0018-9294 (ISSN-L)
  • 1558-2531
DOI
10.1109/tbme.2010.2091640
OpenAlex
W2144723972
Cited by
256
References
42
FWCI
9.19
Type
journal article
Language
en
Open access
green

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