Voice Acoustics as Predictor of Clinical Depression Score

Nik Nur Wahidah Nik Hashim1

  • 1International Islamic University Malaysia

Details

15:05 - 15:20 | Wed 12 Jul | Schmitt Room | WeBT10.4

Session: Voice Frequency Analysis: Expectation for the Convenient but Powerful Diagnostic Tool for Neuropsychiatric Disorders

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Abstract

We explore the reliability of using quantifiable voice acoustic measures for pairwise classification between speech samples of suicidal predisposition, major depressive disorders (MDD) and remitted/healthy subjects. Linear combinations of spectral and timing features of voice was also shown to predict clinical ratings of depression severity measured using the Hamilton Depression Rating Scale (HAMD) and Beck Depression Inventory-II (BDI-II).