Emotion recognition has recently attracted extensive interest due to its significant
applications to human–computer interaction. The expression of human emotion depends on …

Objective There are many barriers to accessing mental health assessments including cost
and stigma. Even when individuals receive professional care, assessments are intermittent …

ChatGPT has shown the potential of emerging general artificial intelligence capabilities, as it
has demonstrated competent performance across many natural language processing tasks …

In the past decade, convolutional neural networks (CNNs) have been widely adopted as the
main building block for end-to-end audio classification models, which aim to learn a direct …

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 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 …

Automatic affect recognition is a challenging task due to the various modalities emotions can
be expressed with. Applications can be found in many domains including multimedia …

Work on voice sciences over recent decades has led to a proliferation of acoustic
parameters that are used quite selectively and are not always extracted in a similar fashion …

Speech emotion recognition is challenging because of the affective gap between the
subjective emotions and low-level features. Integrating multilevel feature learning and model …

The automatic recognition of spontaneous emotions from speech is a challenging task. On
the one hand, acoustic features need to be robust enough to capture the emotional content …