

Polymath
Overview :
Polymath utilizes machine learning to transform any music library (e.g., from your hard drive or YouTube) into a searchable sample library for music production. The tool automatically segments songs into drum beats, bass lines, and other audio elements, quantizes them to the same speed and tempo (e.g., 120 bpm), analyzes musical structure (e.g., chorus, verses), key (e.g., C4, E3), and other information (timbre, loudness, etc.), and converts the audio to MIDI. The result is a streamlined workflow for music producers, DJs, and ML audio developers.
Target Users :
Music production, DJ creation, music database training
Use Cases
Use Polymath to combine elements from different songs to create unique new compositions.
Leverage Polymath's search functionality to quickly find relevant tracks for hour-long DJ sets.
Simplify the process of creating large music datasets for training generative models.
Features
Music source separation using the Demucs neural network
Music structure segmentation/tagging using the sf_segmenter neural network
Music pitch tracking and key detection using the Crepe neural network
Music conversion to MIDI using a fundamental frequency neural network
Music quantization and alignment using pyrubberband
Music information retrieval and processing using librosa
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