Continuous dimensional emotion recognition from speech helps robots or virtual agents
capture the temporal dynamics of a speaker's emotional state in natural human–robot …

Automatic speech emotion recognition (SER) has gained popularity over the last decade
and numerous Challenges have emerged. While the latest Challenges have shown that …

Nonverbal vocalizations contain important affective and communicative information,
especially for those who do not use traditional speech, including individuals who have …

dc. description. abstract There is growing interest in emotion research to model perceived
emotion labelled as intensities along the affect dimensions such as arousal and valence …

Emotional dependencies play a crucial role in understanding complexities of dyadic
interactions. Recent studies have shown that affect recognition tasks can benefit by the …

This thesis outlines novel approaches to integrate contextual information for improving the
performance of automatic emotion recognition systems. Emotion recognition has been of …

Dimensional emotion can better describe rich and fine-grained emotional states than
categorical emotion. In the realm of human–robot interaction, the ability to continuously …

Recognizing user emotions from speech is something humans do naturally when
communicating with each other face-to-face. Machines, however, are still far from perfect …

Computer analysis of human speech can enrich our human-computer interactions. Aside
from automatic speech recognition, which is about translating speech into text, there are …

Feelings, or affect, are a fundamental part of human experience. Arousal and valencemake
up core affect and have received intense study in affective computing. Speechand facial …