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MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech

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References

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2023

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Depression Detection From Social Networks Data Based on Machine Learning and Deep Learning Techniques: An Interrogative Survey

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2023IIFDD: Intra and inter-modal fusion for depression detection with multi-modal information from Internet of Medical Things99 cited

2024Development and application of emotion recognition technology — a systematic literature review97 cited

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2023A systematic review on automated clinical depression diagnosis91 cited

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2023Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A comprehensive review90 cited

2021End-to-end multimodal clinical depression recognition using deep neural networks: A comparative analysis88 cited

2022MFF-SAug: Multi feature fusion with spectrogram augmentation of speech emotion recognition using convolution neural network86 cited

2022Depression recognition using a proposed speech chain model fusing speech production and perception features81 cited

2022TAMFN: Time-Aware Attention Multimodal Fusion Network for Depression Detection78 cited

2023Depression Detection in Speech Using Transformer and Parallel Convolutional Neural Networks75 cited

2023Spatial–Temporal Feature Network for Speech-Based Depression Recognition73 cited

2021Towards Robust Deep Neural Networks for Affect and Depression Recognition from Speech72 cited