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Evaluation of voice acoustics as predictors of clinical depression scores

Nik Hashim, Nik Nur Wahidah and Wilkes, Mitch D. and Salomon, Ronald M. and Meggs, Jared and France, Daniel J. (2016) Evaluation of voice acoustics as predictors of clinical depression scores. Journal of voice, 31 (2). 256.e1-256.e6. ISSN 0892-1997 E-ISSN 1873-4588

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Summary: Objective. The aim of the present study was to determine if acoustic measures of voice, characterizing specific spectral and timing properties, predict clinical ratings of depression severity measured in a sample of patients using the Hamilton Depression Rating Scale (HAMD) and Beck Depression Inventory (BDI-II). Study Design. This is a prospective study. Methods. Voice samples and clinical depression scores were collected prospectively from consenting adult patients who were referred to psychiatry from the adult emergency department or primary care clinics. The patients were audiorecorded as they read a standardized passage in a nearly closed-room environment. MeanAbsolute Error (MAE) between actual and predicted depression scores was used as the primary outcome measure. Results. The average MAE between predicted and actual HAMD scores was approximately two scores for both men and women, and the MAE for the BDI-II scores was approximately one score for men and eight scores for women. Timing features were predictive of HAMD scores in female patients while a combination of timing features and spectral features was predictive of scores in male patients.Timing features were predictive of BDI-II scores in male patients. Conclusion. Voice acoustic features extracted from read speech demonstrated variable effectiveness in predicting clinical depression scores in men and women. Voice features were highly predictive of HAMD scores in men and women, and BDI-II scores in men, respectively. The methodology is feasible for diagnostic applications in diverse clinical settings as it can be implemented during a standard clinical interview in a normal closed room and without strict control on the recording environment. Key Words: depression–severity–prediction–voice–acoustics.

Item Type: Article (Journal)
Additional Information: 7157/61221
Uncontrolled Keywords: depression–severity–prediction–voice–acoustics.
Subjects: R Medicine > R Medicine (General)
T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr Nik Nur Wahidah Nik Hashim
Date Deposited: 25 Jan 2018 16:31
Last Modified: 25 Jan 2018 16:31
URI: http://irep.iium.edu.my/id/eprint/61221

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