Automatic emotion recognition systems predict high-level affective content from low-level
human-centered signal cues. These systems have seen great improvements in classification …

Automated emotion state tracking is a crucial element in the computational study of human
communication behaviors. It is important to design robust and reliable emotion recognition …

The expression and experience of human behavior are complex and multimodal and
characterized by individual and contextual heterogeneity and variability. Speech and …

In this paper, we apply a context-sensitive technique for multimodal emotion recognition
based on feature-level fusion of acoustic and visual cues. We use bidirectional Long Short …

Human emotional expression tends to evolve in a structured manner in the sense that
certain emotional evolution patterns, ie, anger to anger, are more probable than others, eg …

Facial expressions of a person representing similar emotion are not always unique.
Naturally, the facial features of a subject taken from different instances of the same emotion …

In the process of day-to-day learning, expressions are very vital. Detection of human
expressions is growing and has caught the interest of many researchers in the past few …

Articulation, emotion, and personality play strong roles in the orofacial movements. To
improve the naturalness and expressiveness of virtual agents (VAs), it is important that we …

Emotion is expressed and perceived through multiple modalities. In this work, we model
face, voice and head movement cues for emotion recognition and we fuse classifiers using a …

Psycholinguistic studies on human communication have shown that during human
interaction individuals tend to adapt their behaviors mimicking the spoken style, gestures …