Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Gestures that accompany speech are an essential part of natural and efficient embodied
human communication. The automatic generation of such co‐speech gestures is a long …

Multimodal emotion recognition has gained traction in affective computing research
community to overcome the limitations posed by the processing a single form of data and to …

We present the MSP-IMPROV corpus, a multimodal emotional database, where the goal is
to have control over lexical content and emotion while also promoting naturalness in the …

For social robots to effectively engage in human–robot interaction (HRI), they need to be
able to interpret human affective cues and to respond appropriately via display of their own …

Multimodal human–computer interaction (HCI) systems pledge a more human–human-like
interaction between machines and humans. Their prowess in emanating an unambiguous …

This paper introduces UDIVA, a new non-acted dataset of face-to-face dyadic interactions,
where interlocutors perform competitive and collaborative tasks with different behavior …

The exigency of emotion recognition is pushing the envelope for meticulous strategies of
discerning actual emotions through the use of superior multimodal techniques. This work …

The substantial growth of Internet-of-Things technology and the ubiquity of smartphone
devices has increased the public and industry focus on speech emotion recognition (SER) …

Human-computer interactions can be very effective, especially if computers can
automatically recognize the emotional state of the user. A key barrier for effective speech …