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Title page for ETD etd-08152007-120523


Type of Document Dissertation
Author Yingthawornsuk, Thaweesak
Author's Email Address thaweesak.yingthawornsuk@vanderbilt.edu
URN etd-08152007-120523
Title Acoustic analysis of vocal output characteristics for suicidal risk assessment.
Degree PhD
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Richard G.Shiavi Committee Chair
A.B. Bonds III Committee Member
D. Mitchell Wilkes Committee Member
Ralph N. Ohde Committee Member
Ronald M. Salomon Committee Member
Keywords
  • Spectral Energy
  • Vocal Tract
  • Cepstrum
  • GMM
  • Suicide -- Risk factors
  • Depression
  • Suicidal behavior -- Diagnosis
  • Speech -- Measurement
  • Suicidal Speech
  • Depression -- Physiological aspects
Date of Defense 2007-07-26
Availability unrestricted
Abstract
The human voice is a source of important information regarding the physical, psychological, and mental health conditions of a speaker. Acoustic properties of speech have previously been reported as possible cues to risk of committing suicide in persons suffering from severe depression. Certain vocal parameters may be capable of objectively distinguishing depressive speech from near-term suicidal speech. Studies were performed to analyze and statistically compare the speech acoustics of separate female and male samples comprised of subjects attempting suicide and subjects carrying diagnoses of depression and remission (recovery from depression). In this study, two types of speech recordings, spontaneous and reading speech, were collected from each subject of diagnostic groups participating in interview and text-reading sessions. Acoustic analyses of energy distribution within a 0-2,000 Hz frequency range and energy concentration characterizing the vocal tract spectral response based on the Gaussian mixture model (GMM) were performed on speech samples. Discriminant analyses demonstrated the significance of energy distribution and GMM-based vocal features as being effective indicators of perceptual changes in speech production and articulation caused by the severity of psychological state, and as powerful discriminators of diagnostic groups in both female and male studies. Based on the most important pairwise study of depressed and suicidal speech, the 12-fold cross validations yielded the correct classification scores of 86% and 90.33% in classifying spontaneous and reading speech of females, and 86% and 88.50% in classifying male spontaneous and reading speech, respectively. Results suggest the investigated features derived from the reading speech capable of identifying the degree of psychological state as effective as those derived from the spontaneous speech among diagnostic groups.
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