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Title page for ETD etd-03252011-142240


Type of Document Master's Thesis
Author Nik Hashim, Nik Nur Wahidah
Author's Email Address wahidah.hashim@vanderbilt.edu
URN etd-03252011-142240
Title Analysis of power spectrum density of male speech as indicators for high risk and depressed decision
Degree Master of Science
Department Electrical Engineering
Advisory Committee
Advisor Name Title
D. Mitchell Wilkes Committee Member
Ronald M. Salomon Committee Member
Keywords
  • pattern recognition
  • classification
  • PSD
  • spectral energy
  • suicide
  • depression
  • statistical classification
  • suicidal speech
  • applied signal processing
  • resampling
  • speech
Date of Defense 2011-04-05
Availability unrestricted
Abstract
Assessment of a patients risk of committing suicide is important in order for them to be able to receive early hospitalization. The two critical mental states that may arouse much confusion to the clinicians are the high risk suicidal patients and the depressed patients. Current diagnostic tools are time-consuming and require the clinicians to have proper training and experience in order to obtain useful assessment and sufficient information for determining suitable treatments. A lot of information regarding the psychological state is accessible through the human voice content. Our desire is to show the effectiveness of using the Power Spectrum Density of male speech as a potential feature for distinguishing between the high risk suicidal patients and the depressed patients. The classification analyses were performed using the linear and quadratic classifiers together with the three methods of resampling (Equal-Test-Train, Jackknife and Cross-validation). According to the classification results, after removing outlier patients, the feature was shown to be quite effective in identifying between the high risk suicidal patients and the depressed patients.
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