Deep learning for Depression Recognition from Speech

Author:

Tian Han,Zhu ZhangORCID,Jing Xu

Funder

Research Funding of Jinhua Advanced Research Institute

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Information Systems,Software

Reference18 articles.

1. Naujokat E, Perkuhn M, Harris M, Norra C (2009) Depression detection system

2. Rafiqul IM, Ashad KM, Ashir A, Kamal ARM, Hua W, Anwaar U (2018) Depression detection from social network data using machine learning techniques. Health Inf Sci Syst 6(1):8–18

3. Ryder AG, Chentsova-Dutton YE (2012) Depression in china: integrating developmental psychopathology and cultural-clinical psychology. J Clin Child Adolesc Psychol 41(5):682–694

4. He YC, Zhang B, Qu W, Ning J, Quan HY, Xia Y, Yao Y, Han M. (2014) Value of serum monoamine neurotransmitters and their metabolites in diagnosis of comorbid anxiety and depression and major depressive disorder. Journal of third military medical university 36(08):806–810

5. Gunes H, Pantic M (2010) Automatic, dimensional and continuous emotion recognition. Int J Synthetic Emotions 1(1):68–99

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Classification Method for Depression Based on MRI;2023 20th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP);2023-12-15

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