Classifications of clinical depression detection using acoustic measures in Malay speakers

Azam, Huda and Nik Hashim, Nik Nur Wahidah and Sediono, Wahju and Mukhtar, Firdaus and Ibrahim, Normala and Syed Mokhtar, Syarifah Suziah and Abdul Aziz, Salina (2016) Classifications of clinical depression detection using acoustic measures in Malay speakers. In: 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 04 Dec - 08 Dec 2016, Hotel Pullman Kuala Lumpur.

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Abstract

—Objective screening mechanism using paralinguistic cues to enhance current diagnostic on detecting depression is desirable, which resulted in the rise of research on this area. However, to date, there has been no research done using dataset of Malay speakers. This paper presented an acoustic depression detection classification using Linear and Quadratic Discriminant analysis with transition parameters and power spectral density as the acoustic features. Among the two features, power spectral density performed better, especially with the combination of band 1, 2 and 3 for both male and female data. As for the Transition parameters, we found that unvoiced feature performed best overall for both male and female.

Item Type:	Conference or Workshop Item (Invited Papers)
Additional Information:	7157/56813
Uncontrolled Keywords:	Clinical depression, transition parameter, power spectral density, discrimant analysis
Subjects:	Q Science > QP Physiology R Medicine > RF Otorhinolaryngology T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr Nik Nur Wahidah Nik Hashim
Date Deposited:	08 Jun 2017 10:30
Last Modified:	03 Dec 2019 19:39
URI:	http://irep.iium.edu.my/id/eprint/56813

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