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

In this manuscript, the topic of multi-corpus Speech Emotion Recognition (SER) is
approached from a deep transfer learning perspective. A large corpus of emotional speech …

Large, pre-trained neural networks consisting of self-attention layers (transformers) have
recently achieved state-of-the-art results on several speech emotion recognition (SER) …

Recent years have seen a rapid increase in digital medicine research in an attempt to
transform traditional healthcare systems to their modern, intelligent, and versatile …

Foundation models (FMs) are increasingly spearheading recent advances on a variety of
tasks that fall under the purview of computer audition--the use of machines to understand …

Speech emotion recognition (SER) plays a crucial role in understanding user feelings when
developing artificial intelligence services. However, the data mismatch and label distortion …

We revisit the INTERSPEECH 2009 Emotion Challenge--the first ever speech emotion
recognition (SER) challenge--and evaluate a series of deep learning models that are …

Introduction The effective fusion of text and audio information for categorical and
dimensional speech emotion recognition (SER) remains an open issue, especially given the …

In this work, we explore a novel few-shot personalisation architecture for emotional
vocalisation prediction. The core contribution is anenrolment'encoder which utilises two …

In this paper, we explore self-supervised learning (SSL) for analyzing a first-of-its-kind
database of cry recordings containing clinical indications of more than a thousand …