Feature Extraction Method for Predicting Depression by Frequency Domain Analysis

Abstract

Abstract-In this paper, we propose a feature extraction method, which subdivides feature vectors into three frequency regions of 300-1000Hz, 1000-2000Hz, and 2000-3000Hz. The range and mean of intensity are extracted for each frequency region. By so doing, we can compensate the defect of increasing the intensity value, when a person intentionally increases his or her vocalization. Previous studies extracted the slope and correlation of the glottal flow spectrum from the 300-3000Hz region. But, we extract the slope and correlation from each separated frequency region. The overall experimental results show 92.85% for men, and 92.08% for women. The proposed method enhances the respective classification accuracy by 6.73% for men, and 8.09% for women.