Abstract—Evaluation of speakers who are high-risk suicidal
compared to those with less clinical depression are critical when
the syndrome underlying a patient’s abnormal behaviour is
diagnosed without expertise. This study describes a way to
classify the speech samples collected from groups of depressive
and suicidal speakers by employing the speech processing
technique in data analysis. First, the Glottal Spectral Slope
(GSS) and Mel-Frequency Cepstral Coefficients (MFCC) were
computationally estimated from the voiced segments detected
from the categorized speech sample database. Second, the
pairwise classification was then made on the combination of
those extracted vocal features respectively corresponding to the
frequency response of the source and the filter in speech
production system model.
The procedure of this research was carried out in order to
investigate the discriminative property of the focused vocal
parameters mainly between depressed speakers and high-risk
suicidal speaker groups. The result revealed that MFCC and
GSS parameters are slightly high effective in term of vocal
indicator corresponding to severe depression with fairly high
performance in between-group separation.
Index Terms—Depression, glottal spectral slope, MFCC,
speech.
Thaweewong Akkaralaertsest is with Division of Electronics and
Telecommunication Engineering, Faculty of Engineering, Rajamangala
University of Technology KrungThep, Bangkok, Thailand (e-mail:
thaweewong.a@rmutk.ac.th).
Thaweesak Yingthawornsuk is with Media Technology, King Mongkut's
University of Technology Thonburi – Bang Khuntien Campus, Bang
Khuntien, Bangkok, 10150 Thailand (e-mail: thaweesak.yin@kmutt.ac.th).
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Cite:Thaweewong Akkaralaertsest and Thaweesak Yingthawornsuk, "Comparative Analysis of Vocal Characteristics in Speakers with Depression and High-Risk Suicide," International Journal of Computer Theory and Engineering vol. 7, no. 6, pp. 448-452, 2015.
