MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech

Interpreting Depression From Question-Wise Long-Term Video Recording of SDS Evaluation

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Spectral Representation of Behaviour Primitives for Depression Analysis

(2020) Siyang Song et al.   IEEE Transactions on Affective Computing

The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English

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Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features

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Learning Affective Features with a Hybrid Deep Model for Audio-Visual Emotion Recognition

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A review of affective computing: From unimodal analysis to multimodal fusion

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Investigation of different speech types and emotions for detecting depression using different classifiers

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The Economic Burden of Adults With Major Depressive Disorder in the United States (2005 and 2010)

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Detection of Clinical Depression in Adolescents’ Speech During Family Interactions

(2010) Lu-Shih Alex Low et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

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