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

Affective computing is an emerging interdisciplinary research field bringing together
researchers and practitioners from various fields, ranging from artificial intelligence, natural …

Sentiment analysis is an emerging technology that aims to explore people's attitudes toward
an entity. It can be applied in a variety of different fields and scenarios, such as product …

Automatic human affect recognition is a key step towards more natural human-computer
interaction. Recent trends include recognition in the wild using a fusion of audiovisual and …

Speech emotion recognition (SER) is a difficult task due to the complexity of emotions. The
SER performances are heavily dependent on the effectiveness of emotional features …

Speech emotion recognition is a vital and challenging task that the feature extraction plays a
significant role in the SER performance. With the development of deep learning, we put our …

Sentiment analysis aims to automatically uncover the underlying attitude that we hold
towards an entity. The aggregation of these sentiment over a population represents opinion …

Deep learning has emerged as a powerful machine learning technique to employ in
multimodal sentiment analysis tasks. In the recent years, many deep learning models and …

Multimodal emotion recognition (MER) refers to the identification and understanding of
human emotional states by combining different signals, including—but not limited to—text …

The rapid growth of the internet has reached the fourth generation, ie, web 4.0, which
supports Sentiment Analysis (SA) in many applications such as social media, marketing, risk …