The Vibraphone dataset is a carefully curated collection of audio tracks enhanced with precise metadata for a wide range of machine-learning applications. The collection includes the characteristic tones of the vibraphone, a percussion instrument known for its resonating metal bars and dynamic modulation performed via a motor-driven butterfly valve. These characteristics contribute to the vibraphone's distinct and expressive timbre, making it an ideal candidate for training models in generative AI music, Music Information Retrieval (MIR), and source separation.

Exploring the vibraphone's melodic properties shows a compelling combination of resonant metal bars and the subtle vibrato effect provided by the butterfly valve. The resulting sound is both calm and rich, creating a distinct acoustic palette for machine-learning models. With metadata that includes chord progressions, instrumentation details, key signatures, tempo variations, and precise timestamps, our dataset allows your models to capture the complexities of vibraphone performances, improving their ability to generate melodic compositions and extract musical features.