Multimodal Emotion Recognition based on Face and Speech using Deep Convolution Neural Network and Long Short Term Memory

Multimodal emotion recognition (MER) is crucial for analyzing a person’s mental behavior and health to enhance the performance of human–computer-interaction systems. Various deep learning-based MER systems have been presented in the last decade. However, the outcomes of the MER schemes are limited d...

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Veröffentlicht in:	Circuits, systems, and signal processing Jg. 44; H. 9; S. 6622 - 6649
Hauptverfasser:	Taware, Shwetkranti, Thakare, Anuradha D.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2025 Springer Nature B.V
Schlagworte:	Accuracy Artificial neural networks Circuits and Systems Convolution Datasets Deep learning Distance learning Electrical Engineering Electrocardiography Electromyography Electronics and Microelectronics Emotion recognition Emotions Engineering Feature selection Instrumentation Machine learning Neural networks Particle swarm optimization Physiology Real time Reliability Representations Security Semantics Signal,Image and Speech Processing Speech Utility theory Deep learning Affective computing Local binary pattern Multimodal emotion recognition Particle swarm optimization Deep Convolution neural network
ISSN:	0278-081X, 1531-5878
Online-Zugang:	Volltext
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