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

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

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
DOI 10.1109/10.846676
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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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Research works printed but not linked: 9

  1. silverman, 0, From Sound to Silence-A Preliminary Investigation of the Use of Vocal Parameters in the Prediction of Near-Term Suicidal Risk
  2. 10.1037//0033-2909.99.2.143 · DOI
  3. roessler, 1979, vocal patterns in anxieety, Phenomenology and Treatment of Anxiety
  4. silverman, 1992, Vocal parameters as predictors of near-term suicidal risk
  5. juang, 1979, cepstrally based pitch and voicing estimation with statistical assistance homomorphic pitch detector, NSC Note no 140
  6. ostwald, 1963, Soundmaking The Acousical Communication of Emotion
  7. bannister, 1972, An instrumental and judgmental analysis of voice samples from psychiatrically hospitalized and nonhospitalized adolescents
  8. denber, 1978, Sound spectrum analysis of the mentally ill
  9. whitman, 1966, A potential new measurement of emotional state A preliminary report, 17, 167

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Metadata

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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