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What is Mood Disorder Detection via Speech Analysis about?

This document describes a study that proposes an approach for short-term detection of mood disorders based on elicited speech responses. The approach uses an attention-based convolutional neural network to generate emotion profiles for each speech response, and a long short-term memory model with attention to characterize the temporal evolution of emotion profiles across responses. The method achieved an overall accuracy of 75.56% for detecting bipolar disorder and unipolar depression, outperforming other m

Author

Tauqeer Ahmed

Language

EN