Classification of Depression Based on Audio with Artificial Intelligence
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-19951-6_2
Reference35 articles.
1. Alghowinem, S.: From joyous to clinically depressed: mood detection using multimodal analysis of a person’s appearance and speech. In: 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction. pp. 648–654. IEEE (2013)
2. Alghowinem, S. et al.: Multimodal analysis of verbal and nonverbal behaviour on the example of clinical depression (2015)
3. Chao, L., Tao, J., Yang, M., Li, Y.: Multi task sequence learning for depression scale prediction from video. In: 2015 International Conference on Affective Computing and Intelligent Interaction (ACII). pp. 526–531. IEEE (2015)
4. Chlasta, K., Wołk, K., Krejtz, I.: Automated speech-based screening of depression using deep convolutional neural networks. Procedia Comput. Sci. 164, 618–628 (2019)
5. Cummins, N., Epps, J., Breakspear, M., Goecke, R.: An investigation of depressed speech detection: Features and normalization. In: Twelfth Annual Conference of the International Speech Communication Association (2011)
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