Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …

Affective computing is one of the most important research fields in modern human–computer
interaction (HCI). The goal of affective computing is to study and develop the theories …

Multimodal emotion recognition, that is, emotion recognition uses machine learning to
generate multi-modal features on the basis of videos which has become a research hotspot …

Human facial emotion recognition (FER) has attracted the attention of the research
community for its promising applications. Mapping different facial expressions to the …

Automatic emotion recognition has become a trending research topic in the past decade.
While works based on facial expressions or speech abound, recognizing affect from body …

This paper proposes a dynamic facial expression recognition transformer (Former-DFER) for
the in-the-wild scenario. Specifically, the proposed Former-DFER mainly consists of a …

Obtaining large, human labelled speech datasets to train models for emotion recognition is a
notoriously challenging task, hindered by annotation cost and label ambiguity. In this work …

In this paper, a novel approach, which is based on attention guided 3D convolutional neural
networks (CNN)-long short-term memory (LSTM) model, is proposed for speech based …

Many researchers have been seeking robust emotion recognition system for already last two
decades. It would advance computer systems to a new level of interaction, providing much …

Emotions play an essential role in human relationships, and many real‐time applications
rely on interpreting the speaker's emotion from their words. Speech emotion recognition …