Neural network generates convincing songs by famous singers

Jukebox from OpenAI is a generative model that makes music in the same styles as many artists you’ll probably recognize:

To train this model, we crawled the web to curate a new dataset of 1.2 million songs (600,000 of which are in English), paired with the corresponding lyrics and metadata from LyricWiki. The metadata includes artist, album genre, and year of the songs, along with common moods or playlist keywords associated with each song. We train on 32-bit, 44.1 kHz raw audio, and perform data augmentation by randomly downmixing the right and left channels to produce mono audio.

A lot of the time, generative music sounds artificial and mechanical, but these results are pretty convincing. I mean you can still tell it’s not from the artist, but many of the examples are listenable.

OpenAI also published the code.