references.bib

% References for the evaluation thresholds used in the Hardanger fiddle AMT paper.
% Origin of standard MIREX/MAESTRO note-tracking thresholds (50 ms onset,
% max(50 ms, 20% duration) offset, 50 cents pitch).

@inproceedings{bay2009mirex,
  author    = {Mert Bay and Andreas F. Ehmann and J. Stephen Downie},
  title     = {Evaluation of Multiple-{F0} Estimation and Tracking Systems},
  booktitle = {Proceedings of the 10th International Society for Music Information Retrieval Conference (ISMIR)},
  pages     = {315--320},
  address   = {Kobe, Japan},
  year      = {2009},
  url       = {https://ismir2009.ismir.net/proceedings/PS2-21.pdf},
}

@inproceedings{raffel2014mireval,
  author    = {Colin Raffel and Brian McFee and Eric J. Humphrey and Justin Salamon and Oriol Nieto and Dawen Liang and Daniel P. W. Ellis},
  title     = {{mir\_eval}: A Transparent Implementation of Common {MIR} Metrics},
  booktitle = {Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR)},
  pages     = {367--372},
  address   = {Taipei, Taiwan},
  year      = {2014},
  url       = {https://archives.ismir.net/ismir2014/paper/000320.pdf},
}

@inproceedings{hawthorne2018onsets,
  author    = {Curtis Hawthorne and Erich Elsen and Jialin Song and Adam Roberts and Ian Simon and Colin Raffel and Jesse Engel and Sageev Oore and Douglas Eck},
  title     = {Onsets and Frames: Dual-Objective Piano Transcription},
  booktitle = {Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR)},
  pages     = {50--57},
  address   = {Paris, France},
  year      = {2018},
  url       = {https://archives.ismir.net/ismir2018/paper/000019.pdf},
}

@inproceedings{hawthorne2019maestro,
  author    = {Curtis Hawthorne and Andriy Stasyuk and Adam Roberts and Ian Simon and Cheng-Zhi Anna Huang and Sander Dieleman and Erich Elsen and Jesse Engel and Douglas Eck},
  title     = {Enabling Factorized Piano Music Modeling and Generation with the {MAESTRO} Dataset},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year      = {2019},
  url       = {https://arxiv.org/abs/1810.12247},
}