Critical Analysis of the Impact of Glottal Features in the Classification of Clinical Depression in Speech

The motivation for this work is in an attempt to rectify the current lack of objective tools for clinical analysis of emotional disorders. This study involves the examination of a large breadth of objectively measurable features for use in discriminating depressed speech. Analysis is based on featur...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2008-01, Vol.55 (1), p.96-107
Main Authors: Moore II, Elliot, Clements, Mark A., Peifer, John W., Weisser, Lydia
Format: Article
Language:English
Subjects:
Affect
Biomedical computing
Biomedical engineering
depression
Depressive Disorder - complications
Depressive Disorder - diagnosis
Depressive Disorder - physiopathology
Diagnosis, Computer-Assisted - methods
glottal
Glottis - physiopathology
Humans
Medical services
Medical treatment
Mood
Oral communication
Pattern analysis
prosodics
Reproducibility of Results
Sensitivity and Specificity
Sound Spectrography - methods
Speech analysis
Speech Disorders - diagnosis
Speech Disorders - etiology
Speech Disorders - physiopathology
Speech Production Measurement - methods
Stress
vocal tract
Voice Quality
voice source
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Summary:The motivation for this work is in an attempt to rectify the current lack of objective tools for clinical analysis of emotional disorders. This study involves the examination of a large breadth of objectively measurable features for use in discriminating depressed speech. Analysis is based on features related to prosodics, the vocal tract, and parameters extracted directly from the glottal waveform. Discrimination of the depressed speech was based on a feature selection strategy utilizing the following combinations of feature domains: prosodic measures alone, prosodic and vocal tract measures, prosodic and glottal measures, and all three domains. The combination of glottal and prosodic features produced better discrimination overall than the combination of prosodic and vocal tract features. Analysis of discriminating feature sets used in the study reflect a clear indication that glottal descriptors are vital components of vocal affect analysis.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2007.900562