  Recent directions in automatic speech recognition (ASR) research have shown
that applying deep learning models from image recognition challenges in
computer vision is beneficial. As automatic music transcription (AMT) is
superficially similar to ASR, in the sense that methods often rely on
transforming spectrograms to symbolic sequences of events (e.g. words or
notes), deep learning should benefit AMT as well. In this work, we outline an
online polyphonic pitch detection system that streams audio to MIDI by
ConvLSTMs. Our system achieves state-of-the-art results on the 2007 MIREX
multi-F0 development set, with an F-measure of 83\% on the bassoon, clarinet,
flute, horn and oboe ensemble recording without requiring any musical language
modelling or assumptions of instrument timbre.
