ItemConference Paper

Deep Learning for Mental Health: Attention-Driven Multilayer CNN for Audio Depression Detection

Title
Deep Learning for Mental Health: Attention-Driven Multilayer CNN for Audio Depression Detection
Creator
Joy, Salna; Krishna, B.V. Santhosh; Rajesh, Siddharth; Neethu, P.S.
Description
Depressive Disorder is a common mental health problem that affects millions of people around the world. This study proposes a Self-attention based Multi-layer Convolutional Neural Network (CNN) model to perform enhanced depression detection from audio modality. The model employs a diverse array of filters, kernel sizes, and pooling strategies across multiple CNN layers to capture local features, while the attention mechanism prioritizes emotionally salient parts of the speech signal, such as regions of low energy and lengthened pauses by assigning higher weights. Measured against the RAVDESS and TESS emotional speech datasets, the method attains an F1 score of 0.81, an accuracy of 83% and ROC-AUC of 0.96 when using attention, beating the baseline CNN model, F1 score of 0.77 and 83% accuracy without attention. The results demonstrate the effectiveness of attention-enhanced architectures in detecting depressive cues from speech and support the feasibility of developing real-world, speech-based mental health screening tools. 2025 IEEE.
Source
International Conference on Intelligent Communication Networks and Computational Techniques, ICICNCT 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
attention mechanism; audio depression detection; deep learning; mental health screening; multi-layer convolutional neural networks (CNN)
Coverage
Joy S., New Horizon College of Engineering, Department of Electronics and Communication Engineering, Bengaluru, India; Krishna B.V.S., New Horizon College of Engineering, Department of Electronics and Communication Engineering, Bengaluru, India; Rajesh S., New Horizon College of Engineering, Department of Electronics and Communication Engineering, Bengaluru, India; Neethu P.S., School of Engineering and Technology, Christ University, Department of Aiml and Data Science, Bengaluru, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833158623-2;
Format
online
Language
English
Type
Conference paper

Citation

Joy, Salna; Krishna, B.V. Santhosh; Rajesh, Siddharth; Neethu, P.S., “Deep Learning for Mental Health: Attention-Driven Multilayer CNN for Audio Depression Detection,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 17, 2026, https://archives.christuniversity.in/items/show/26016.

Output Formats