Music Generation AI


MuseNet is a deep neural network that uses unsupervised learning to generate 4-minute musical compositions with 10 different instruments and blend styles from country to Mozart to the Beatles. With advanced mode, you can directly interact with the model to create an entirely new piece, while simple mode lets you explore the variety of musical styles the model can create. MuseNet uses long-term structure with training from classical archives, BitMidi, and the MAESTRO dataset. Join OpenAI in testing their innovative music generation technology.

Screenshot for MuseNet

Project Description

OpenAI has created MuseNet, a revolutionary deep neural network for music composition. The network has been trained to generate 4-minute music compositions with as many as ten different instruments such as country, the Mozart style, and even the Beatles. MuseNet has the capability of combining different styles to generate new compositions. The network was not programmed with pre-existing music knowledge but rather used unsupervised learning’s general-purpose technology like GPT-2. MuseNet can even combine Chopin’s Nocturne with pop-style music and generate new compositions. The density of the model allows it to remember long-term structures while creating new pieces, and it also utilizes multiple embeddings to give more context to the model. Moreover, MuseNet has two modes; simple and advanced, allowing people with different skill levels to generate their music. However, the model has limitations in generating odd pairings of styles and instruments. The samples generated by the model can be found on OpenAI’s platform, and people are encouraged to tweet their creations through Instaudio. The possibilities of this technology are endless, and OpenAI is excited to see how it will revolutionize the music industry.