Sentiment analysis as a field has come a long way since it was first introduced as a task
nearly 20 years ago. It has widespread commercial applications in various domains like …

With the advancement of multimedia and human-computer interaction, it has become
increasingly crucial to perceive people's emotional states in dynamic data (eg, video, audio …

Continuous affect recognition is becoming an increasingly attractive research topic in
affective computing. Previous works mainly focused on modelling the temporal dependency …

Despite the increasing research interest in end-to-end learning systems for speech emotion
recognition, conventional systems either suffer from the overfitting due in part to the limited …

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

This study introduces a method to design a curriculum for machine-learning to maximize the
efficiency during the training process of deep neural networks (DNNs) for speech emotion …

Continuous dimensional emotion recognition from speech helps robots or virtual agents
capture the temporal dynamics of a speaker's emotional state in natural human–robot …

Multimodal dimensional emotion recognition has drawn a great attention from the affective
computing community and numerous schemes have been extensively investigated, making …

Continuous emotion recognition has been a compelling topic in affective computing
because it can interpret human emotions subtly and continuously. Existing studies have …

Despite remarkable advances in emotion recognition, they are severely restrained from
either the essentially limited property of the employed single modality, or the synchronous …