While speech emotion recognition (SER) has been an active research field since the last
three decades, the techniques that deal with the natural environment have only emerged in …

Sentiment analysis (SA) aims to understand the attitudes and views of opinion holders with
computers. Previous studies have achieved significant breakthroughs and extensive …

Multimodal fusion has been proved to improve emotion recognition performance in previous
works. However, in real-world applications, we often encounter the problem of missing …

Emotion recognition in conversation is a crucial topic for its widespread applications in the
field of human-computer interactions. Unlike vanilla emotion recognition of individual …

There has been a recent explosion of large-scale image-text datasets, as images with alt-
text captions can be easily obtained online. Obtaining large-scale, high quality data for video …

The proliferation of edge computing and the Internet of Vehicles (IoV) has significantly
bolstered the popularity of deep learning-based driver assistance applications. This has …

Rumor spreaders are increasingly utilizing multimedia content to attract the attention and
trust of news consumers. Though quite a few rumor detection models have exploited the …

Automated multimodal emotion recognition has become an emerging but challenging
research topic in the fields of affective learning and sentiment analysis. The existing works …

With the development of both hardware and deep neural network technologies, tremendous
improvements have been achieved in the performance of automatic emotion recognition …

Emotion recognition is a challenging and actively-studied research area that plays a critical
role in emotion-aware human-computer interaction systems. In a multimodal setting …