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.
Audio diffusion model by Harmonai for generating music samples.
Music generation model using masked acoustic token modeling.
Real-time music generation using Stable Diffusion on spectrograms.
Open-source toolkit for audio, music, and speech generation research.
Open-source music generation model for creating full songs with vocals and accompaniment.
Updated music generation model with improved quality and longer generation.
Original latent diffusion model for text-to-audio generation.
Latent diffusion model for text-to-audio, music, and speech generation.
Stability AI training and inference code for generative audio models including diffusion and LMs.
Audio super-resolution model for upsampling audio to higher sample rates.
Transformer-based text-to-audio model by Suno supporting speech, music, and sound effects.
High-fidelity neural audio codec by Meta for audio compression and tokenization.
Text-to-music generation model using cascaded latent diffusion.
Audio processing toolkit building on Whisper for diarization and subtitling.
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.
Fast music generation model producing full songs with lyrics in seconds.
High-fidelity universal neural audio codec by Descript for compression.
PyTorch library for deep learning research on audio generation including MusicGen and AudioGen.