UNDERSTANDING EMOTIONS WITH DEEP LEARNING: A MULTIMODAL APPROACH FOR DETECTING SPEECH AND FACIAL EXPRESSIONS

Authors

  • Kondragunta Rama Krishnaiah, Harish H

Keywords:

Emotion Recognition, Multimodal Learning, Speech Emotion Recognition (SER), Facial Emotion Recognition (FER), Convolutional Neural Networks (CNN).

Abstract

Emotion recognition plays a crucial role in enhancing human-machine interactions, allowingsystems to engage with users in a more intuitive and empathetic manner. Despite advancementsin artificial intelligence

References

Bjorn S, Stefan S, Anton B, Alessandro V, Klaus S, Fabien R, Mohamed C, Felix W, Florian E, Erik M, Marcello M, Hugues S, Anna P, Fabio V, Samuel K (2013) Interspeech 2013 Computational Paralinguistics Challenge: Social Signals, Conflict, Emotion, Autism

Deepak G, Joonwhoan L (2013) Geometric feature-based facial expression recognition in image sequences using multi-class AdaBoost and support vector machines. Sensors 13:7714– 7734.

Downloads

Published

2024-01-16

How to Cite

Kondragunta Rama Krishnaiah, Harish H. (2024). UNDERSTANDING EMOTIONS WITH DEEP LEARNING: A MULTIMODAL APPROACH FOR DETECTING SPEECH AND FACIAL EXPRESSIONS. Journal of Computational Analysis and Applications (JoCAAA), 32(1), 661–673. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2666

Issue

Vol. 32 No. 1 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.