Emotion Datasets

Emotion datasets are crucial for training and evaluating models that recognize and understand emotions expressed through various modalities, such as speech, text, and music. Current research focuses on improving the generalizability of emotion recognition models across diverse datasets and languages, often employing transformer-based architectures and addressing challenges like data imbalance and annotation inconsistencies. This work is significant for advancing human-computer interaction, enabling more nuanced and empathetic AI systems, and providing valuable tools for research in fields like psychology, education, and finance.