Meta's AudioCraft Adds JASCO and MusicGen-Style for Precise Music Control
Meta's open-source audio generation library bundles MusicGen, AudioGen, EnCodec, MAGNeT, JASCO and AudioSeal into one PyTorch toolkit for text-to-music research.
- AudioCraft bundles MusicGen, AudioGen, EnCodec, MAGNeT, MBD, AudioSeal, MusicGen-Style and JASCO in one PyTorch library.
- JASCO adds flow-matching text-to-music with chord, drum and melody timing conditions.
- JASCO ships in 400M and 1B sizes, trained on roughly 16K hours of licensed music.
- MusicGen-Style conditions a 1.5B transformer on a 1.5 to 4.5 second audio reference plus text.
- Code is MIT licensed; model weights are CC-BY-NC 4.0 and restricted to non-commercial use.
- Requires Python 3.9 and PyTorch 2.1.0; MusicGen-Style needs a 16 GB GPU for inference.
AudioCraft adds timeline and style controls to generative audio
Meta’s Fundamental AI Research team has expanded the AudioCraft repository into a PyTorch stack for music generation, sound generation, neural audio compression, diffusion decoding, and watermarking. Its newer JASCO and MusicGen-Style models add time-aligned musical controls and reference-audio conditioning.
Developers can use shared audio processing, configuration, training, and inference infrastructure across several generation architectures. That common foundation reduces the work required to compare models, build new conditioning methods, or train compatible weights.
Eight components, one codebase
The repository groups eight components around common PyTorch and EnCodec tooling:
| Component | Purpose | Key detail |
|---|---|---|
| MusicGen | Text-to-music generation | Autoregressive Transformer available in 300M, 1.5B, and 3.3B parameter sizes |
| AudioGen | Text-to-sound generation | Produces sound effects and environmental audio |
| EnCodec | Neural audio compression | Converts waveforms into compact tokens used by the generators |
| Multi Band Diffusion | Audio decoding | Uses diffusion to decode EnCodec representations |
| MAGNeT | Music and sound generation | Uses non-autoregressive masked modeling to generate multiple tokens in parallel |
| AudioSeal | Audio watermarking | Embeds and detects localized watermarks in generated audio |
| MusicGen-Style | Text-and-style-to-music generation | Conditions generation on text and a short reference clip |
| JASCO | Structurally controlled music generation | Accepts text, timed chords, drum tracks, and melodies |
JASCO puts controls on the timeline
JASCO accepts a global text description alongside time-aligned local conditions. A prompt can specify instrumentation or character, while chord events, drums, and melody define musical structure at particular points in the clip. This design supports experiments that measure whether generated music follows both semantic and temporal instructions.
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