A survey of speech emotion recognition in natural environment
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 …
three decades, the techniques that deal with the natural environment have only emerged in …
Sentiment analysis: Comprehensive reviews, recent advances, and open challenges
Sentiment analysis (SA) aims to understand the attitudes and views of opinion holders with
computers. Previous studies have achieved significant breakthroughs and extensive …
computers. Previous studies have achieved significant breakthroughs and extensive …
CTNet: Conversational transformer network for emotion recognition
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 …
field of human-computer interactions. Unlike vanilla emotion recognition of individual …
Learning audio-video modalities from image captions
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 …
text captions can be easily obtained online. Obtaining large-scale, high quality data for video …
Missing modality imagination network for emotion recognition with uncertain missing modalities
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 …
works. However, in real-world applications, we often encounter the problem of missing …
Inconsistent matters: A knowledge-guided dual-consistency network for multi-modal rumor detection
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 …
trust of news consumers. Though quite a few rumor detection models have exploited the …
C-GCN: Correlation based graph convolutional network for audio-video emotion recognition
With the development of both hardware and deep neural network technologies, tremendous
improvements have been achieved in the performance of automatic emotion recognition …
improvements have been achieved in the performance of automatic emotion recognition …
Multimodal emotion recognition with temporal and semantic consistency
Automated multimodal emotion recognition has become an emerging but challenging
research topic in the fields of affective learning and sentiment analysis. The existing works …
research topic in the fields of affective learning and sentiment analysis. The existing works …
Group gated fusion on attention-based bidirectional alignment for multimodal 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 …
role in emotion-aware human-computer interaction systems. In a multimodal setting …
Modeling hierarchical uncertainty for multimodal emotion recognition in conversation
Approximating the uncertainty of an emotional AI agent is crucial for improving the reliability
of such agents and facilitating human-in-the-loop solutions, especially in critical scenarios …
of such agents and facilitating human-in-the-loop solutions, especially in critical scenarios …