The day is fast approaching when generative AI won’t only write and create images in a convincingly human-like style, but compose music and sounds that pass for a professional’s work, too.

This morning, Meta announced AudioCraft, a framework to generate what it describes as “high-quality,” “realistic” audio and music from short text descriptions, or prompts. It’s not Meta’s first foray into audio generation — the tech giant open sourced an AI-powered music generator, MusicGen, in June — but Meta claims that it’s made advances that vastly improve the quality of AI-generated sounds, such as dogs barking, cars honking and footsteps on a wooden floor.

In a blog post shared with TechCrunch, Meta explains that the AudioCraft framework was designed to simplify the use of generative models for audio compared to prior work in the field (e.g. Riffusion, Dance Diffusion and OpenAI’s Jukebox). AudioCraft, the code for which is available in open source, provides a collection of sound and music generators plus compression algorithms that can be used to create and encode songs and audio without having to switch between different codebases.AudioCraft contains three generative AI models: MusicGen, AudioGen and EnCodec.

MusicGen isn’t new. But Meta’s released the training code for it, enabling users to train the model on their own dataset of music.

That could raise major ethical and legal issues, considering MusicGen “learns” from existing music to produce similar effects — a fact with which not all artists or generative AI users are comfortable.

Increasingly, homemade tracks that use generative AI to conjure familiar sounds that can be passed off as authentic, or at least close enough, have been going viral. Music labels have been quick to flag them to streaming partners, citing intellectual property concerns — and they’ve generally been victorious. But there’s still a lack of clarity on whether “deepfake” music violates the copyright of artists, labels and other rights holders.