MuseNet
OpenAI Blog
OpenAI created MuseNet, a neural network that generates 4-minute musical compositions across 10 different instruments by learning patterns from hundreds of thousands of MIDI files. The model produces coherent pieces that blend musical styles ranging from country to Mozart to the Beatles without explicit programming of musical rules. MuseNet uses the same transformer architecture as GPT-2, demonstrating that general-purpose sequence prediction can apply to music composition as well as text.
Why it matters
We’ve created MuseNet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI files. MuseNet uses the same general-purpose unsupervised technology as GPT-2, a large-scale transformer model trained to predict the next token in a sequence, whether audio or text.
