This paper is in the following e-collection/theme issue:

Web-based and Mobile Health Interventions (3693) Mobile Health (mhealth) (3196) Depression and Mood Disorders; Suicide Prevention (1541) Machine Learning (1780) Text-messaging (SMS, WeChat etc)-Based Interventions (701) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (94)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34474, first published .
Automatic Depression Detection Using Smartphone-Based Text-Dependent Speech Signals: Deep Convolutional Neural Network Approach

Automatic Depression Detection Using Smartphone-Based Text-Dependent Speech Signals: Deep Convolutional Neural Network Approach

Automatic Depression Detection Using Smartphone-Based Text-Dependent Speech Signals: Deep Convolutional Neural Network Approach

Authors of this article:

Ah Young Kim1 Author Orcid Image ;   Eun Hye Jang1 Author Orcid Image ;   Seung-Hwan Lee2, 3, 4 Author Orcid Image ;   Kwang-Yeon Choi5 Author Orcid Image ;   Jeon Gue Park6, 7 Author Orcid Image ;   Hyun-Chool Shin8 Author Orcid Image
Article Authors Cited by (39) Tweetations (6) Metrics

Journals

  1. Guo K, Xiao Y, Deng W, Zhao G, Zhang J, Liang Y, Yang L, Liao G. Speech disorders in patients with Tongue squamous cell carcinoma: A longitudinal observational study based on a questionnaire and acoustic analysis. BMC Oral Health 2023;23(1) View
  2. Ksibi A, Zakariah M, Menzli L, Saidani O, Almuqren L, Hanafieh R. Electroencephalography-Based Depression Detection Using Multiple Machine Learning Techniques. Diagnostics 2023;13(10):1779 View
  3. Shekar P, Mathew A, Yeswanth P, Deivalakshmi S. A combined deep CNN-RNN network for rainfall-runoff modelling in Bardha Watershed, India. Artificial Intelligence in Geosciences 2024;5:100073 View
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  12. Naveed S, Husnain M, Samad A, Ikram A, Afreen H, Gilanie G, Alsubaie N. Drug Efficacy Recommendation System of Glioblastoma (GBM) Using Deep Learning. IEEE Access 2025;13:10398 View
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  14. El Hallani A, Chakhtouna A, Adib A. Advanced speech biomarker integration for robust Alzheimer’s disease diagnosis. Annals of Telecommunications 2025;80(5-6):427 View
  15. Su Z, Jiang H, Yang Y, Hou X, Su Y, Yang L. Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach. Journal of Medical Internet Research 2025;27:e67772 View
  16. Jia X, Chen J, Liu K, Wang Q, He J. Multimodal depression detection based on an attention graph convolution and transformer. Mathematical Biosciences and Engineering 2025;22(3):652 View
  17. Zhou Y, Yu X, Huang Z, Palati F, Zhao Z, He Z, Feng Y, Luo Y. Multi-Modal Fused-Attention Network for Depression Level Recognition Based on Enhanced Audiovisual Cues. IEEE Access 2025;13:37913 View
  18. Kumari M, Singh G, Pande S. A Survey of Current Progress in Depression Detection Using Deep Learning and Machine Learning. Biomedical Materials & Devices 2025 View
  19. Dawadi R, Inoue M, Tay J, Martin-Morales A, Vu T, Araki M. Disease Prediction Using Machine Learning on Smartphone-Based Eye, Skin, and Voice Data: Scoping Review. JMIR AI 2025;4:e59094 View
  20. Shah S, Gillani S, Baig M, Saleem M, Siddiqui M. Advancing depression detection on social media platforms through fine-tuned large language models. Online Social Networks and Media 2025;46:100311 View
  21. Yang M, Ngai E, Hu X, Hu B, Liu J, Gelenbe E, Leung V. Digital Phenotyping and Feature Extraction on Smartphone Data for Depression Detection. Proceedings of the IEEE 2024;112(12):1773 View
  22. Li C, Zhang K, Lin Q, Huang S, Cheng W, Lei Y, Zhao X, Zhao J. Major depressive disorder recognition based on electronic handwriting recorded in psychological tasks. BMC Medicine 2025;23(1) View
  23. Briganti G, Lechien J. Speech and Voice Quality as Digital Biomarkers in Depression: A Systematic Review. Journal of Voice 2025 View
  24. Chen D, Wang P, Zhang X, Qiao R, Li N, Zhang X, Zhang H, Wang G. Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study. JMIR Formative Research 2025;9:e56057 View
  25. Amorese T, Cuciniello M, Greco C, Sheveleva O, Cordasco G, Glackin C, McConvey G, Callejas Z, Esposito A. Detecting depression in speech using verbal behavior analysis: a cross-cultural study. Frontiers in Psychology 2025;16 View
  26. Yang Y, Zheng W. Multi-level spatiotemporal graph attention fusion for multimodal depression detection. Biomedical Signal Processing and Control 2025;110:108123 View

Books/Policy Documents

  1. Verma R, Kumar G, Yadav A. Proceedings of International Conference on Recent Innovations in Computing. View
  2. Singh D, Rani M, Kumari S, Kumar R, Priya V, Singh R. Machine Learning for Social Transformation. View
  3. Jin R, Zhao Y, Chen L, Geng Z, Wang S, Zheng L. Applied Intelligence. View

Conference Proceedings

  1. Srinivasan J, Vishnu A, M G, Pragna N, Polavarapu R. 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA). Unleashing the Potential of Convolutional Neural Networks for Automated Depression Detection Using Audio Modality View
  2. Bankar O, Rajput Y, Kumbhar V, Singh T. 2023 International Conference on Integration of Computational Intelligent System (ICICIS). Machine Learning Applications in Depression Research: A Comprehensive Review and Analysis View
  3. Naregalkar P, Shinde A, Patil M. 2023 International Conference on Computational Intelligence, Networks and Security (ICCINS). Depression Diagnosis Using Linear Features Based on EEG Signals View
  4. Sharma A, Saxena A, Kumar A, Singh D. 2024 2nd International Conference on Disruptive Technologies (ICDT). Depression Detection Using Multimodal Analysis with Chatbot Support View
  5. Kanoujia S, Karuppanan P. 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). Depression Detection in Speech Using ML and DL Algorithm View
  6. El Hallani A, Chakhtouna A, Adib A. 2024 IEEE 12th International Symposium on Signal, Image, Video and Communications (ISIVC). Speech as a Window to the Brain: Innovative Techniques in Early Alzheimer’s Disease Detection View
  7. Tasnim M, Ramos R, Stroulia E, Trejo L. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). A Machine-Learning Model for Detecting Depression, Anxiety, and Stress from Speech View
  8. P D, Sri Devi R. 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT). Empowering Women's Mental Health: A Critical Examination Of Depression Detection View
  9. Shwetha C, Pushpalatha K. 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). Corpus Creation and Annotating Multilingual Code-Mixed Kannada English Data with Precise Labels for Depression Detection View
  10. Kongchatree K, Suriyo O, Pichedpan N, Kongkachandra R, Songmuang P. 2025 IEEE International Conference on Cybernetics and Innovations (ICCI). Machine Learning Models for Speech-Based Depression Screening View