CNN-BASED MULTIMODAL EMOTION DETECTION: INTEGRATING SPEECH RECOGNITION AND FACIAL EXPRESSION ANALYSIS
DOI:
https://doi.org/10.48047/Keywords:
Human-Computer Interaction, Multimodal Emotion Detection, Rule-Based Systems, Convolutional Neural Networks.Abstract
Accurate identification and interpretation of human emotions are critical in the modern world of affective computing and human-computer interaction. The paper presents a state-of-the-art multimodal emotion detection system that incorporates the most recent methods for facial expression analysis, speech recognition, and video processing. Conventional techniques for identifying emotions have shown shortcomings, especially when it comes to accurately representing the complex and ever changing emotional states of people. Taking these difficulties into account, this study aims to create a solid framework that effectively blends several modalities to improve the precision of emotion identification.
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Domínguez-Jiménez JA, Campo-Landines KC, Martínez-Santos J, Delahoz EJ, Contreras-Ortiz S (2020) A machine learning model for emotion recognition from physiological signals. Biomed Signal Proces 55:101646
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