Audio based depression detection using Convolutional Autoencoder

•A novel audio-based depression detection system using Convolutional Autoencoder.•Convolutional Autoencoder for extracting highly correlated and compact feature set.•Thorough experimental study based on a real-world depression detection dataset.•Complete comparison of proposed feature extraction met...

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Veröffentlicht in:	Expert systems with applications Jg. 189; S. 116076
Hauptverfasser:	Sardari, Sara, Nakisa, Bahareh, Rastgoo, Mohammed Naim, Eklund, Peter
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 01.03.2022 Elsevier BV
Schlagworte:	Artificial neural networks Audio data Audio depression detection Classification Convolutional Autoencoder Early depression detection Feature extraction Machine learning Mental disorders Pattern recognition Performance evaluation Sampling methods Semi-supervised learning Audio depression detection Early depression detection Semi-supervised learning Convolutional Autoencoder
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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