The FuturePop dataset is a collection of audio files with precise metadata such as chords, instrumentation, key, tempo, and date. This dataset was selected primarily for machine learning applications such as generative AI music, Music Information Retrieval (MIR), and source separation. Future pop music is essentially an electronic-pop fusion genre that defies traditional boundaries. It features advanced synthesizers, experimental beats, and unorthodox structures, creating a distinct sound world.

Our dataset captures the genre's innovative essence, allowing your models to grasp the intricacies and changing patterns in future pop music. By training your machine learning models with this dataset, you engage them in the distinct sounds that define the newest forms of musical expression, allowing for originality and pushing the bounds of innovation. Harness the power of future pop, propel your machine learning projects forward, and allow your AI systems to resonate with tomorrow's forward-thinking sounds.