In recent years, foundation models (FMs) such as large language models (LLMs) and latent
diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This …

Self-supervised learning (SSL) has recently emerged as a promising paradigm for training
generalisable models on large-scale data in the fields of vision, text, and speech. Although …

In the era of extensive intersection between art and Artificial Intelligence (AI), such as image
generation and fiction co-creation, AI for music remains relatively nascent, particularly in …

In this paper, we explore the application of Large Language Models (LLMs) to the pre-
training of music. While the prevalent use of MIDI in music modeling is well-established, our …

Self-supervised learning (SSL) has recently emerged as a promising paradigm for training
generalisable models on large-scale data in the fields of vision, text, and speech. Although …

Learning music representations that are general-purpose offers the flexibility to finetune
several downstream tasks using smaller datasets. The wav2vec 2.0 speech representation …

A novel 3D auto-drum machine system for the generation and recording of percussion
sounds is developed and presented. The capabilities of the machine, along with a …

Audio classification plays a crucial role in speech and sound processing tasks with a wide
range of applications. There still remains a challenge of striking the right balance between …

Cardiovascular disease screening is critically anchored in heart sound auscultation. As
deep learning methodologies advance, the impetus toward automating heart sound …

Singing voice is one of the most essential elements of music. It provides impactful emotional
expressions through melody and lyrics and has the potential to move people's hearts and …