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
Link To Document