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Human and machine recognition of the vocal characteristics of suicide

dc.creatorSinha, Abhraneel
dc.date.accessioned2020-08-23T16:04:38Z
dc.date.available2015-12-19
dc.date.issued2013-12-19
dc.identifier.urihttps://etd.library.vanderbilt.edu/etd-12022013-124213
dc.identifier.urihttp://hdl.handle.net/1803/15036
dc.description.abstractSuicide is a major health problem in the US, and has become an important topic of study. Recently, psychiatrists have reported hearing a particular sound or tonality in the voices of subjects that are at high risk of attempting suicide. This has lead to research to discriminate between depression and this high risk state based on the acoustic properties of the subject's voice, and has lead to some very promising results. Many of the features that have been used for this task are based on the power spectrum of the voice; however, it is not clear whether these features have captured the particular tonality that the psychiatrists have reported. The whole work attempts to address this question through analysis of speech data by calculating the harmonics, amplitudes, and other discriminating features from 6 depressed and 6 high risk subjects.
dc.format.mimetypeapplication/pdf
dc.subjectSuicide
dc.subjectSpeech
dc.subjectDSP
dc.titleHuman and machine recognition of the vocal characteristics of suicide
dc.typethesis
dc.contributor.committeeMemberDr. Ronald M.Saloman
dc.type.materialtext
thesis.degree.nameMS
thesis.degree.levelthesis
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorVanderbilt University
local.embargo.terms2015-12-19
local.embargo.lift2015-12-19
dc.contributor.committeeChairDr. D.Mitchell Wilkes


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