Automated depression detection from human speech using acoustic feature analysis and deep learning
A novel multimodal depression recognition framework that combines handcrafted acoustic characteristics with deep learning-based representations of Mel spectrograms is proposed, highlighting the potential of AI-based speech recognition as a scalable and objective preliminary mental health screening tool.