Cited by 504Emotion and Mood RecognitionVoice and Speech DisordersSpeech Recognition and Synthesis

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Acoustical properties of speech as indicators of depression and suicidal risk

France, D.J., Shiavi, R.G., Silverman, S., Silverman, M., Wilkes, M.·2000·IEEE Transactions on Biomedical Engineering

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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 (Fo), 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 Fo were generally ineffective discriminators in both studies. The results support theories that identify psychomotor disturbances as central elements in depression and suicidality.

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Authors: France, D. J., Shiavi, R. G., Silverman, S., Silverman, M., & Wilkes, M.
Affiliations: L-3 Communications (United States) (US)
Vanderbilt University (US)
Norwalk Hospital (US)
Venue: IEEE Transactions on Biomedical Engineering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2000-07
Volume: 47
Issue: 7
Pages: 829-837
ISSN: 0018-9294 (ISSN-L)
DOI: 10.1109/10.846676
OpenAlex: W2148822124
Cited by: 504
References: 41
Citations by year: 2026: 16 · 2025: 30 · 2024: 31 · 2023: 37 · 2022: 34 · 2021: 45 · 2020: 41 · 2019: 25 · 2018: 34 · 2017: 27 · 2016: 26 · 2015: 27 · 2014: 23 · 2013: 25 · 2012: 17
FWCI: 2.16
Type: journal article
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Transactions on Biomedical Engineering (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Health Sciences › Health Professions › Speech and Hearing › Voice and Speech Disorders
Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
Keywords: speech acoustics, depression, suicide risk, voice fundamental frequency, amplitude modulation, formants, power spectral density, dysthymia, major depressive disorder, sex differences, psychomotor disorders
MeSH terms: Suicide Prevention, Adult, Biomedical Engineering, Depression, Female, Humans, Male, Middle Aged, Risk Factors, Speech Acoustics, Suicide, Case-Control Studies

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Acoustical properties of speech as indicators of depression and suicidal risk

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