Polymath is an open-source toolkit that converts existing music libraries into structured, searchabl
Polymath is an open-source toolkit that converts existing music libraries into structured, searchable sample libraries using machine learning. Built in Python and Jupyter notebooks, it focuses on large-scale audio analysis, segmentation, and feature extraction to transform full songs into usable stems, loops, and one-shots for music production. The project integrates tools such as Madmom, Librosa, Pydub, and FFmpeg to perform tasks like onset detection, beat tracking, tempo estimation, and key detection.
Polymath organizes extracted samples into a database with rich metadata, enabling efficient search and retrieval based on tempo, key, instrument characteristics, or other audio features. It supports batch processing of large collections, making it useful for producers, DJs, sound designers, and researchers who want to repurpose personal or licensed libraries into production-ready material. Because it is code-driven, Polymath is best suited for technically inclined users comfortable with Python and command-line workflows, and for developers who want a customizable framework for music information retrieval and dataset creation.
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