Significant progress has been made in symbolic music generation with the help of deep
learning techniques. However, the tasks covered by symbolic music generation have not …

This survey paper provides a comprehensive overview of the recent advancements and
challenges in applying large language models to the field of audio signal processing. Audio …

Generating music from text descriptions is a user-friendly mode since the text is a relatively
easy interface for user engagement. While some approaches utilize texts to control music …

AI-empowered music processing is a diverse field that encompasses dozens of tasks,
ranging from generation tasks (eg, timbre synthesis) to comprehension tasks (eg, music …

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 …

Dynamic sparsity, where the sparsity patterns are unknown until runtime, poses a significant
challenge to deep learning. The state-of-the-art sparsity-aware deep learning solutions are …

Pre-trained language models have achieved impressive results in various music
understanding and generation tasks. However, existing pre-training methods for symbolic …

Although deep learning has revolutionized music generation, existing methods for structured
melody generation follow an end-to-end left-to-right note-by-note generative paradigm and …

Music is one of the Gardner's intelligences in his theory of multiple intelligences. How
humans perceive and understand music is still being studied and is crucial to develop …

When editing a video a piece of attractive background music is indispensable. However
video background music generation tasks face several challenges for example the lack of …