Fetching the paper…
Reading the bibliography…
We advance the state of the art in polyphonic piano music transcription by using a deep convolutional and recurrent neural network which is trained to jointly predict onsets and frames.
Calculation of a constant q spectral transform
Judith C Brown · 1991
Earlier work this paper cites.
Bidirectional recurrent neural networks
Mike Schuster and Kuldip K Paliwal · 1997
Earlier work this paper cites.
Non-negative matrix factorization for polyphonic music transcription
Paris Smaragdis and Judith C Brown · 2003
Earlier work this paper cites.
Finding intensities of individual notes in piano music
Wai Man Szeto, Kin Hong Wong, and Chi Hang Wong · 2005
Earlier work this paper cites.
Evaluation of multiple-f0 estimation and tracking systems
Mert Bay, Andreas F Ehmann, and J Stephen Downie · 2009
Earlier work this paper cites.
Multipitch estimation of piano sounds using a new probabilistic spectral smoothness principle
Valentin Emiya, Roland Badeau, and Bertrand David · 2010
Earlier work this paper cites.
Estimating note intensities in music recordings
Sebastian Ewert and Meinard Müller · 2011
Earlier work this paper cites.
Polyphonic piano note transcription with recurrent neural networks
Sebastian Böck and Markus Schedl · 2012
Earlier work this paper cites.
Automatic music transcription: challenges and future directions
Emmanouil Benetos, Simon Dixon, Dimitrios Giannoulis, Holger Kirchhoff, and Anssi Klapuri · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
Cited alongside, same era.
mir_eval: A transparent implementation of common mir metrics
Colin Raffel, Brian McFee, Eric J. Humphrey, Justin Salamon, Oriol Nieto, Dawen Liang, and Daniel P. W. Ellis · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
Cited alongside, same era.
Predicting expressive dynamics in piano performances using neural networks
Sam Van Herwaarden, Maarten Grachten, and Bas De Haas · 2014
Cited alongside, same era.
Tensorflow: Large-scale machine learning on heterogeneous distributed systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al · 2016
Cited alongside, same era.
An end-to-end neural network for polyphonic piano music transcription
Siddharth Sigtia, Emmanouil Benetos, and Simon Dixon · 2016
Later among the works it cites.
Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
Later among the works it cites.
Music transcription with a convolutional neural network 2016
Daylin Troxel · 2016
Later among the works it cites.
Piano transcription with convolutional sparse lateral inhibition
Andrea Cogliati, Zhiyao Duan, and Brendt Wohlberg · 2017
Closest in time.
Polyphonic piano note transcription with non-negative matrix factorization of differential spectrogram
Lufei Gao, Li Su, Yi-Hsuan Yang, and Tan Lee · 2017
Closest in time.
Learning features of music from scratch
John Thickstun, Zaid Harchaoui, and Sham Kakade · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
An attack/decay model for piano transcription
Tian Cheng, Matthias Mauch, Emmanouil Benetos, Simon Dixon, et al · 2016
Cited alongside, same era.
Piano transcription in the studio using an extensible alternating directions framework
Sebastian Ewert and Mark Sandler · 2016
Cited alongside, same era.
On the potential of simple framewise approaches to piano transcription
Rainer Kelz, Matthias Dorfer, Filip Korzeniowski, Sebastian Böck, Andreas Arzt, and Gerhard Widmer · 2016
Cited alongside, same era.
librosa: v0.4.3, May 2016
Brian McFee · 2016
Cited alongside, same era.
Closest in time.
Polyphonic pitch detection with convolutional recurrent neural networks
Carl Thomé and Sven Ahlbäck · 2017
Closest in time.
A two-stage approach to note-level transcription of a specific piano
Qi Wang, Ruohua Zhou, and Yonghong Yan · 2017
Closest in time.