A Universal Music Translation Network

Understand

We present a method for translating music across musical instruments, genres, and styles.

• This method is based on a multi-domain wavenet autoencoder, with a shared encoder and a disentangled latent space that is trained end-to-end on waveforms.
• Employing a diverse training dataset and large net capacity, the domain-independent encoder allows us to translate even from musical domains that were not seen during training.
• The method is unsupervised and does not rely on supervision in the form of matched samples between domains or musical transcriptions.