Speech-based automatic depression detection systems have been extensively explored
over the past few years. Typically, each speaker is assigned a single label (Depressive or …

Speech emotion recognition (SER) plays a pivotal role in enhancing Human-computer
interaction (HCI) systems. This paper introduces a groundbreaking Capsule-enhanced …

Understanding human emotions is necessary for various tasks, including interpersonal
interaction, knowledge acquisition, and determining courses of action. Recognizing …

Speech is usually used for constructing an automatic Alzheimer's dementia (AD) detection
system, as the acoustic and linguistic abilities show a decline in people living with AD at the …

Cross-domain speech emotion recognition (SER) has received increasing attention in recent
years. Existing transfer subspace learning and regression-based SER methods have the …

In speech emotion recognition, existing models often struggle to accurately classify emotions
with high similarity. In this paper, we propose a novel architecture that integrates a multi …

With the support of multi-head attention, the Transformer shows remarkable results in
speech emotion recognition. However, existing models still suffer from the inability to …

Speech emotion recognition has been widely used in many applications such as call centres
and mental health monitoring. However, speech emotion recognition still faces great …

Large, pretrained model architectures have demonstrated potential in a wide range of audio
recognition and classification tasks. These architectures are increasingly being used in …

Automatic depression detection systems based on speech signals have recently garnered
significant attention. Depression modeling from speech signals, however, faces three …