SONITRA
A controlled benchmarking toolkit for automatic music transcription that systematically varies acoustic factors to separate algorithmic limitations from recording artefacts.
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Filtered by: Audio-Processing
Learning Normal Patterns in Musical Loops
An unsupervised framework for analyzing audio patterns in musical loops through anomaly detection. Combines HTS-AT feature extraction with Deep SVDD to learn normal patterns without labeled training data, addressing variable-length audio challenges.
READ MORE north_eastMIDI Loop Extraction for Symbolic Music Datasets
A Python package for extracting instrument-specific musical loops from MIDI datasets. Implements a modular pipeline for bass, guitar, piano, drums, and synthesizer parts with configurable filtering and multiple output formats.
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