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In the use of deep neural networks, it is crucial to provide appropriate input representations for the network to learn from.
“Musical genre classification of audio signals,”
George Tzanetakis and Perry Cook, · 2002
Earlier work this paper cites.
“On rhythm and general music similarity.,”
Tim Pohle, Dominik Schnitzer, Markus Schedl, Peter Knees, and Gerhard Widmer, · 2009
Earlier work this paper cites.
“Cyclic tempogram—a mid-level tempo representation for musicsignals,”
Peter Grosche, Meinard Müller, and Frank Kurth, · 2010
Earlier work this paper cites.
“Scikit-learn: Machine learning in python,”
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al., · 2011
Earlier work this paper cites.
“The million song dataset,”
Thierry Bertin-Mahieux, Daniel PW Ellis, Brian Whitman, and Paul Lamere, · 2011
Earlier work this paper cites.
“Maximum filter vibrato suppression for onset detection,”
Sebastian Böck and Gerhard Widmer, · 2013
Earlier work this paper cites.
“End-to-end learning for music audio,”
Sander Dieleman and Benjamin Schrauwen, · 2014
Earlier work this paper cites.
“Adam: A method for stochastic optimization,”
Diederik Kingma and Jimmy Ba, · 2014
Earlier work this paper cites.
“Modeling musical rhythmatscale with the music genome project,”
Matthew Prockup, Andreas F Ehmann, Fabien Gouyon, Erik M Schmidt, and Youngmoo E Kim, · 2015
Cited alongside, same era.
“Batch normalization: Accelerating deep network training by reducing internal covariate shift,”
Sergey Ioffe and Christian Szegedy, · 2015
Cited alongside, same era.
“Learning temporal features using a deep neural network and its application to music genre classification.,”
Il-Young Jeong and Kyogu Lee, · 2016
Cited alongside, same era.
“Feature learning for chord recognition: the deep chroma extractor,”
Filip Korzeniowski and Gerhard Widmer, · 2016
Cited alongside, same era.
“Wavenet: A generative model for raw audio,”
Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu, · 2016
Cited alongside, same era.
“Scale and shift invariant time/frequency representation using auditory statistics: Application to rhythm description,”
Ugo Marchand and Geoffroy Peeters, · 2016
Later among the works it cites.
“A tutorial on deep learning for music information retrieval,”
Keunwoo Choi, György Fazekas, Kyunghyun Cho, and Mark Sandler, · 2017
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“Designing efficient architectures for modeling temporal features with convolutional neural networks,”
Jordi Pons and Xavier Serra, · 2017
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“Sample-level deep convolutional neural networks for music auto-tagging using raw waveforms,”
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan Nam, · 2017
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“Transfer learning for music classification and regression tasks,”
Keunwoo Choi, György Fazekas, Mark Sandler, and Kyunghyun Cho, · 2017
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“Automatic tagging using deep convolutional neural networks,”
Keunwoo Choi, György Fazekas, and Mark Sandler, · 2016
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.
“The extended ballroom dataset,”
Ugo Marchand and Geoffroy Peeters, · 2016
Cited alongside, same era.
“A post-processing procedure for improving music tempo estimates using supervised learning,”
Hendrik Schreiber,
Cited in the paper.
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“librosa 0.5. 0,” 2017
Brian McFee, Matt McVicar, Oriol Nieto, Stefan Balke, Carl Thome, Dawen Liang, Eric Battenberg, Josh Moore, Rachel Bittner, Ryuichi Yamamoto, et al., · 2017
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“The effects of noisy labels on deep convolutional neural networks for music classification,”
Keunwoo Choi, György Fazekas, Kyunghyun Cho, and Mark Sandler, · 2017
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“A comparison on audio signal preprocessing methods for deep neural networks on music tagging,”
Keunwoo Choi, George Fazekas, Kyunghyun Cho, and Mark Sandler, · 2017
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