Music & Audio Generation AI Tools
Open-source tools for generating music, sound effects, and audio from text or other inputs.
Open-source tools for generating music, sound effects, and audio from text or other inputs.
Audio generation framework by Meta including MusicGen for text-to-music.
State-of-the-art music source separation model by Meta for splitting tracks.
Open-source toolkit for audio, music, and speech generation research.
Original latent diffusion model for text-to-audio generation.
High-fidelity neural audio codec by Meta for audio compression and tokenization.
Text-to-music generation model using cascaded latent diffusion.
Latent diffusion model for text-to-audio, music, and speech generation.
Real-time music generation using Stable Diffusion on spectrograms.
Open-weight audio generation model by Stability AI for sound effects and production elements.
Full-length song generation model using diffusion with lyrics and style conditioning.
Open-source music generation model for creating full songs with vocals and accompaniment.
Audio super-resolution model for upsampling audio to higher sample rates.
High-fidelity universal neural audio codec by Descript for compression.
Music generation model using masked acoustic token modeling.
Audio diffusion model by Harmonai for generating music samples.
Transformer-based text-to-audio model by Suno supporting speech, music, and sound effects.
Audio processing toolkit building on Whisper for diarization and subtitling.
PyTorch library for deep learning research on audio generation including MusicGen and AudioGen.
Updated music generation model with improved quality and longer generation.
Stability AI training and inference code for generative audio models including diffusion and LMs.
Fast music generation model producing full songs with lyrics in seconds.