Multitask Learning for Polyphonic Piano Transcription, a Case Study
Rainer Kelz, Sebastian Böck, Cierhard Widnaer · 2019
Viewing polyphonic piano transcription as a multitask learning problem, where we need to simultaneously predict onsets, intermediate frames and offsets of notes, we investigate the performance impact of additional prediction targets, using a variety of suitable convolutional neural network architectures. We quantify performance differences of additional objectives on the larGe MAESTRO dataset.