Reggaeton is an edited set of audio files with rich information that may be used in machine-learning applications across multiple domains. Reggaeton, which originated in Puerto Rico in the late 1990s, smoothly integrates reggae, dancehall, hip hop, and Latin American influences, creating in a distinct genre with a dembow rhythm and energetic beats. With recordings tagged for chords, instrumentation, key, tempo, and timestamps, this dataset is an excellent resource for training models in generative AI music, Music Information Retrieval (MIR), and source separation.

Reggaeton's global prominence, especially since the early 2000s, has made it a major player in the Latin music scene. The dataset's focus on reggaeton enables machine learning models to grasp the genre's intricacies, allowing for the construction of AI-generated compositions and facilitating tasks such as source separation, which provides insights into the many layers of sound within reggaeton songs. This dataset, with its rich annotations, offers up new paths for research and development, providing a unique opportunity to explore the lively and rhythmic world of reggaeton via the lens of machine learning.