A person's behavior significantly influences their health and well-being. It also contributes to
the social environment in which humans interact, with cascading impacts to the health and …

A coupled multimodal emotional feature analysis (CMEFA) method based on broad–deep
fusion networks, which divide multimodal emotion recognition into two layers, is proposed …

This paper considers the problem of anomaly detection in an outdoor environment where
surveillance cameras are usually installed to monitor activities of general public. A novel …

The Graph Convolutional Neural Networks (GCN) method has shown excellent performance
in the field of deep learning, and using graphs to represent speech data is a computationally …

The motivation for this work is to contribute to the collection of large in-the-wild multimodal
datasets in which the speech of the subject is affected by certain medical conditions. Our …

Detecting mental states of human users is crucial for the development of cooperative and
intelligent robots, as it enables the robot to understand the user's intentions and desires …

This paper presents a novel approach to audio-visual consistency judgment (AVCJ), in
which vowel-like regions exhibiting significant changes in lip shape are used as key …

A person's social intelligence impacts their physical and mental health, and the productivity
levels of the individuals involved, for example, in workplace interactions. To promote …

In this work, a supervised probabilistic approach is proposed that integrates the learning
using privileged information (LUPI) paradigm into a hidden conditional random field (HCRF) …

Hidden conditional random fields (HCRFs) are a powerful supervised classification system,
which is able to capture the intrinsic motion patterns of a human action. However, finding the …