A Comprehensive Review of Unimodal and Multimodal Emotion Detection: Datasets, Approaches, and Limitations

View Full Paper

Ask AI

Bookmark

Authors

Discussion

This review examines emotion detection techniques in facial and speech modalities, highlighting datasets and challenges.

MAIN FINDING: Integrating multimodal data significantly enhances emotion detection accuracy using deep learning methods.
KEY EVIDENCE: Models trained on synchronized audio and video datasets show improved performance in recognizing emotions.
APPROACH: The review covers traditional machine learning and state-of-the-art deep learning techniques in emotion detection.
SIGNIFICANCE: This resource guides researchers in selecting the best datasets and models for advanced emotional AI applications.

Thakur et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark