Omnizart: A General Toolbox for Automatic Music Transcription
Yu‐Te Wu, Yin-Jyun Luo, Tsung-Ping Chen, I‐Chieh Wei, Jui-Yang Hsu, Yi-Chin Chuang, Li Su · The Journal of Open Source Software · 2021
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 toolkit that offers transcription models for various music content including piano solo, instrument ensembles, percussion and vocal.Omnizart also supports models for chord recognition and beat/downbeat tracking, which are highly related to AMT.In summary, Omnizart incorporates:• Pre-trained models for frame-level and note-level transcription of multiple pitched instruments, vocal melody, and drum events; • Pre-trained models of chord recognition and beat/downbeat tracking; • The main functionalities in the life-cycle of AMT research, covering dataset downloading, feature pre-processing, model training, to the sonification of the transcription result.Omnizart is based on Tensorflow (Abadi et al., 2016).The complete code base, commandline interface, documentation, as well as demo examples can all be accessed from the project website.