Abstract
Multimodal emotion recognition involves the integration of data from multiple sources Deep learning, or modalities, such as facial expressions, vocal tone, body language, and physiological signals. This holistic approach aims to capture a more accurate and comprehensive understanding of emotional states. Deep learning, with its ability to extract intricate patterns from diverse data types, has become an invaluable tool in this pursuit.
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