An Experimental Analysis of the Entanglement Problem in Neural-Network-based Music Transcription Systems

@article{Kelz2017AnEA,
  title={An Experimental Analysis of the Entanglement Problem in Neural-Network-based Music Transcription Systems},
  author={Rainer Kelz and Gerhard Widmer},
  journal={CoRR},
  year={2017},
  volume={abs/1702.00025}
}
Several recent polyphonic music transcription systems have utilized deep neural networks to achieve state of the art results on various benchmark datasets, pushing the envelope on framewise and note-level performance measures. Unfortunately we can observe a sort of glass ceiling effect. To investigate this effect, we provide a detailed analysis of the particular kinds of errors that state of the art deep neural transcription systems make, when trained and tested on a piano transcription task… CONTINUE READING
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