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the Korean Institute of Electrical Engineers
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2021-12
(Vol.70P No.04)
10.5370/KIEEP.2021.70.4.277
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REF
References
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M. H. Jana, Mar 2019, Text-Based Detection of the Risk of Depression, Front. Psychol. 10:513, pp. 1-11
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K. S. Kim, Dec 2017, Development of depression diagnosis system using EEG signal, Journal of the Korea Academia-Industrial cooperation Society, Vol. 18, No. 12, pp. 452-458
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Yan Zhao, Nov 2021, Detecting Depression from Speech through an Attentive LSTM Network, IEICE TRANS. INF. & SYST., vol. E104-D, Vol. no. 11, pp. 2019-2023
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H. Wang, Sep 2021, Depression Speech Recognition With a Three-Dimensional Convolutional Network, Front. Hum. Neurosci. 15:713823, pp. 1-15
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A. Waghela, Jun 2020, Depression Detection using speech as Input Signal, International Journal of Future Generation Communication and Networking, Vol. 13, No. 3, pp. 1275-1286
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K. Swathy, J. Anju, July 2020, Speech Based Depression Detection using Convolution Neural Networks, International Journal of Innovative Technology and Exploring Engineering (IJITEE), Vol. 9, No. 9, pp. 2278-3075
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H.W Choee, Oct 2019, CNN-based Speech Emotion Recognition using Transfer Learning, Journal of Korean Institute of Intelligent Systems, Vol. 29, No. 5, pp. 339-334
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S. Hershey, Jan 2017, CNN architectures for large-scale audio classification, IEEE International Conference on Acoustics Speech and Signal Processing, pp. 131-135
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Z. S. Syed, Nov 2020, Deep Acoustic Embeddings for Identifying Parkinsonian Speech, International Journal of Advanced Computer Science and Applications(IJACSA), Vol. 11, No. 10, pp. 726-734
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H. A. Andrew, Apr 2017, MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications, arXiv preprint arXiv:1704.04861, pp. 1-9