Emotion Intensity

Emotion intensity research focuses on understanding and modeling the nuanced strength of emotions expressed in various modalities, such as speech, text, and facial expressions. Current research employs diverse approaches, including deep learning models like transformers and recurrent neural networks, often incorporating multimodal data fusion (audio-visual) and techniques like best-worst scaling for improved annotation and intensity prediction. This work is significant for advancing affective computing, enabling more realistic and expressive human-computer interaction, and improving applications in areas like mental health assessment and speech synthesis.