Attention-Based Acoustic Feature Fusion Network for Depression Detection
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This repository contains the implementation of our proposed ABAFnet, a novel integrated speech feature attention-based recurrent network for efficient depression detection and analysis. The main goal of this project is to provide an accurate and efficient approach for detecting depression using speech data.
Note: The code we released is not compelete in some detail due to the data privacy, but the model structure parts are Complete Edition. For our concern about data privacy, we have hidden the part about the data.
Clone the repository
git clone https://github.com/xuxiaoooo/ABAFnet.git
cd ABAFnet@article{xu2024attention,
title={Attention-based acoustic feature fusion network for depression detection},
author={Xu, Xiao and Wang, Yang and Wei, Xinru and Wang, Fei and Zhang, Xizhe},
journal={Neurocomputing},
pages={128209},
year={2024},
publisher={Elsevier}
}