  We are investigating the broader concept of using AI-based generative music
systems to generate training data for Music Information Retrieval (MIR) tasks.
To kick off this line of work, we ran an initial experiment in which we trained
a genre classifier on a fully artificial music dataset created with MusicGen.
We constructed over 50 000 genre- conditioned textual descriptions and
generated a collection of music excerpts that covers five musical genres. Our
preliminary results show that the proposed model can learn genre-specific
characteristics from artificial music tracks that generalise well to real-world
music recordings.
