Survey on Current Trend in Emotion Recognition Techniques Using Deep Learning

Abstract

Deep learning techniques have been used by many researchers to address various challenges in the field, such as the recognition of subtle and complex emotions, the reduction of subjectivity and inter-annotator variability, and the improvement of recognition accuracy. This research paper provides a comprehensive survey of the current trends in emotion recognition techniques using deep learning. It also addresses the ethical and social challenges, as well as their implications for the creation and deployment of emotion recognition models. The study concludes by summarizing the key findings and providing insights into the future direction of research in emotion recognition using deep learning. The paper suggests that the development of more sophisticated deep learning models, the integration of multiple modalities, and the integration of physiological signals with behavioral signals are promising avenues for future research.