Perceptual details of depression detection in Romanian language

Automatic detection of a depression state, studying voice inflexions and speech prosody, is carried out in this paper, using data extracted from the vocalic analysis of formants. We've done an important number of tests for depression detection using a K-Nearest Neighborhood algorithm run upon two databases with professional and normal voices recorded on selected texts in Romanian language. The selected stories were relevant for generating negative emotion (in our case depression). Our tests gave interesting results which have a large variety of possible applications.

[1]  Horia-Nicolai Teodorescu,et al.  ANALYZING EMOTIONS IN SPOKEN ROMANIAN , 2007 .

[2]  Ioan Pavaloi,et al.  Emotion recognition in audio records , 2013, International Symposium on Signals, Circuits and Systems ISSCS2013.

[3]  Paul Boersma,et al.  Praat, a system for doing phonetics by computer , 2002 .

[4]  J. Mundt,et al.  Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology , 2007, Journal of Neurolinguistics.

[5]  Horia-Nicolai Teodorescu,et al.  SRoL - Web-based Resources for Languages and Language Technology e-Learning , 2010, International Journal of Computers Communications & Control.

[6]  Mihaela Costin,et al.  Improving cochlear implant performances by MFCC technique , 2003, Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on.

[7]  Horia-Nicolai L. Teodorescu,et al.  A Study on Speech with Manifest Emotions , 2007, TSD.

[8]  Robert Jean Campbell Campbell's Psychiatric Dictionary , 2003 .