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

Speech emotion recognition (SER) is traditionally performed using merely acoustic
information. Acoustic features, commonly are extracted per frame, are mapped into emotion …

Recent advances in transformer-based architectures have shown promise in several
machine learning tasks. In the audio domain, such architectures have been successfully …

Automatic emotion recognition is one of the central concerns of the Human-Computer
Interaction field as it can bridge the gap between humans and machines. Current works train …

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

Emotion detection holds significant importance in facilitating human–computer interaction,
enhancing the depth of engagement. By integrating this capability, we pave the way for …

Automatic emotion recognition plays a key role in computer-human interaction as it has the
potential to enrich the next-generation artificial intelligence with emotional intelligence. It …

With regard to human–machine interaction, accurate emotion recognition is a challenging
problem. In this paper, efforts were taken to explore the possibility to complete the feature …

With new developments in the field of human–computer interaction, researchers are now
paying attention to emotion recognition, especially multimodal emotion recognition, as …

Data augmentation techniques have recently gained more adoption in speech processing,
including speech emotion recognition. Although more data tend to be more effective, there …