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

Affective Computing systems can detect the emotional state and mindset of an individual.
Speech Emotion Recognition (SER) is a unimodal affect computing system based on …

There is an imminent need for guidelines and standard test sets to allow direct and fair
comparisons of speech emotion recognition (SER). While resources, such as the Interactive …

In this study, we analyze the use of speech and speaker recognition technologies and
natural language processing to detect Alzheimer disease (AD) and estimate mini-mental …

An efficient, low-complexity, and anchor-free object detector based on the state-of-the-art
YOLO framework is proposed in this paper, which can be implemented in real time on edge …

Speech Emotion Recognition (SER) refers to the recognition of human emotions from
natural speech. If done accurately, it can offer a number of benefits in building human …

In recent studies, self-supervised pre-trained models tend to outperform supervised pre-
trained models in transfer learning. In particular, self-supervised learning of utterance-level …

Speech emotion recognition (SER) plays a vital role in intelligent human–computer
interaction (HCI). The Convolutional Neural Network (CNN) is widely used in SER …

Speech emotion recognition (SER) has widespread applications in human-computer
interaction. However, the performance of SER models often drops in domain mismatch …

Emotion recognition through speech is a technique employed in various scenarios of
Human–Computer Interaction (HCI). Existing approaches have achieved significant results; …