2k citations · 4.6k across the 27 of their papers we have counts for
6 papers · 1 filter
Live Music Models
Lyria Team, Antoine Caillon, Brian McWilliams +33
We introduce a new class of generative models for music called live music models that produce a continuous stream of music in real-time with synchronized user control. We release M…
Towards Learning Universal Audio Representations
Luyu Wang, Pauline Luc, Yan Wu +8
The ability to learn universal audio representations that can solve diverse speech, music, and environment tasks can spur many applications that require general sound content under…
Multimodal Self-Supervised Learning of General Audio Representations
Luyu Wang, Pauline Luc, Adria Recasens +2
We present a multimodal framework to learn general audio representations from videos. Existing contrastive audio representation learning methods mainly focus on using the audio mod…
Multi-Format Contrastive Learning of Audio Representations
Luyu Wang, Aaron van den Oord
Recent advances suggest the advantage of multi-modal training in comparison with single-modal methods. In contrast to this view, in our work we find that similar gain can be obtain…
The challenge of realistic music generation: modelling raw audio at scale
Sander Dieleman, Aäron van den Oord, Karen Simonyan
Realistic music generation is a challenging task. When building generative models of music that are learnt from data, typically high-level representations such as scores or MIDI ar…
Efficient Neural Audio Synthesis
Nal Kalchbrenner, Erich Elsen, Karen Simonyan +7
Sequential models achieve state-of-the-art results in audio, visual and textual domains with respect to both estimating the data distribution and generating high-quality samples. E…