Emotion Attribute

Emotion attribute research focuses on accurately identifying and modeling the various components of emotional expression in speech and text. Current efforts concentrate on improving the reliability and robustness of emotion recognition systems, particularly addressing challenges like inconsistent human labeling and speaker variability, often employing deep learning architectures like CNNs and Bayesian approaches such as evidential regression. This work is crucial for advancing applications such as emotional speech synthesis and improving the fairness and accuracy of large language models by mitigating biases in emotion attribution.