The Charango Dataset is a comprehensive collection of audio tracks paired with detailed metadata, curated to drive advancements in machine learning applications across various domains. This dataset offers a systematic exploration into the captivating world of charango music, showcasing the instrument's unique timbre, melodic intricacies, and cultural significance.

Originating from the Andean regions of South America, the charango has emerged as a prominent instrument in traditional folk music and contemporary genres alike. Each audio track within this dataset captures the nuanced nuances and emotive qualities of the charango, providing a diverse array of material for analysis and research endeavors.

Accompanying the audio recordings are detailed metadata annotations, offering insights into musical structures, instrumentation, key signatures, tempo variations, timestamps, and other pertinent details. This comprehensive metadata empowers machine learning models to discern the intricacies of charango performances, facilitating tasks such as generative music composition, music information retrieval (MIR), source separation, and beyond. The Charango Dataset serves as an invaluable resource for researchers, musicians, and developers seeking to explore the unique characteristics of the charango within the realm of machine learning, enabling innovative approaches to music synthesis, analysis, and interpretation.