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Jukebox stands as an open-source neural network tool revolutionizing music creation by generating raw audio and basic singing across multiple genres and artist styles. It releases code and model weights along with an exploration tool for generated samples.

Enabling users to input genre, artist, and lyrics preferences, Jukebox responds with new music samples spanning various styles and artists, even generalizing to unfamiliar lyrics.

This tool produces music that diverges significantly from its training songs when conditioned on lyrics seen during training. Utilizing 12 seconds of audio input, Jukebox completes the remainder in a specified style.

Jukebox models music directly as raw audio, a complex task due to the extensive length of raw audio sequences. Addressing this challenge, it employs an autoencoder to compress raw audio into a lower-dimensional space, enabling audio generation within that compressed space before up-sampling back to raw audio.

Distinguished from symbolic music generation tools like piano rolls, Jukebox pushes the boundaries of generative models, offering heightened expressiveness.

Ideal for enthusiasts exploring AI-generated music, Jukebox represents an innovative leap in music generation, fostering creativity across diverse styles and genres.


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