Omnizart: A General Toolbox for Automatic Music Transcription
This addresses the problem for researchers and practitioners in music information retrieval by offering a general toolbox, though it is incremental as it builds on existing deep learning methods.
The authors tackled the lack of a comprehensive and user-friendly tool for automatic music transcription by releasing Omnizart, a Python library that provides a streamlined solution covering a wide range of instruments and related tasks, resulting in the first such toolkit with models for solo, ensemble, percussion, vocal, chord recognition, and beat/downbeat tracking.
We present and release Omnizart, a new Python library that provides a streamlined solution to automatic music transcription (AMT). Omnizart encompasses modules that construct the life-cycle of deep learning-based AMT, and is designed for ease of use with a compact command-line interface. To the best of our knowledge, Omnizart is the first transcription toolkit which offers models covering a wide class of instruments ranging from solo, instrument ensembles, percussion instruments to vocal, as well as models for chord recognition and beat/downbeat tracking, two music information retrieval (MIR) tasks highly related to AMT.