Fetching the paper…
Reading the bibliography…
Deep Neural Network-based source separation methods usually train independent models to optimize for the separation of individual sources.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Multitask learning
R. Caruana · 1997
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
Performance measurement in blind audio source separation
E. Vincent, R. Gribonval, and C. Févotte · 2006
Earlier work this paper cites.
Combining pitch-based inference and non-negative spectrogram factorization in separating vocals from polyphonic music
T. Virtanen, A. Mesaros, and M. Ryynänen · 2008
Earlier work this paper cites.
Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation
A. Ozerov and C. Févotte · 2010
Earlier work this paper cites.
Rectifier nonlinearities improve neural network acoustic models
A. L. Maas, A. Y. Hannun, and A. Y. Ng · 2013
Earlier work this paper cites.
Speech-guided source separation using a pitch-adaptive guide signal model
R. Hennequin, J. J. Burred, S. Maller, and P. Leveau · 2014
Earlier work this paper cites.
Discriminatively trained recurrent neural networks for single-channel speech separation
F. Weninger, J. R. Hershey, J. Le Roux, and B. Schuller · 2014
Earlier work this paper cites.
Singing-voice separation from monaural recordings using deep recurrent neural networks
P.-S. Huang, M. Kim, M. Hasegawa-Johnson, and P. Smaragdis · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Cited alongside, same era.
Batch normalization: accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
Deconvolution and checkerboard artifacts
A. Odena, V. Dumoulin, and C. Olah · 2016
Cited alongside, same era.
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick, R. Pascanu, N. Rabinowitz, J. Veness, G. Desjardins, A. A. Rusu, K. Milan, J. Quan, T. Ramalho, A. Grabska-Barwinska, D. Hassabis, C. Clopath, D. Kumaran, and R. Hadsell · 2017
Later among the works it cites.
The 2018 signal separation evaluation campaign
F.-R. Stöter, A. Liutkus, and N. Ito · 2018
Later among the works it cites.
Audio Source Separation
C. Févotte, E. Vincent, and A. Ozerov · 2018
Later among the works it cites.
S. I. Mimilakis, K. Drossos, J. Santos, G. Schuller, T. Virtanen, and Y. Bengio · 2018
Later among the works it cites.
Music source separation using stacked hourglass networks
S. Park, T. Kim, K. Lee, and N. Kwak · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Improving music source separation based on deep neural networks through data augmentation and network blending
S. Uhlich, M. Porcu, F. Giron, M. Enenkl, T. Kemp, N. Takahashi, and Y. Mitsufuji · 2017
Cited alongside, same era.
Monoaural audio source separation using deep convolutional neural networks
P. Chandna, M. Miron, J. Janer, and E. Gómez · 2017
Cited alongside, same era.
Singing voice separation with deep u-net convolutional networks
A. Jansson, E. Humphrey, N. Montecchio, R. Bittner, A. Kumar, and T. Weyde · 2017
Cited alongside, same era.
Multi-scale multi-band densenets for audio source separation
N. Takahashi and Y. Mitsufuji · 2017
Cited alongside, same era.
Wave-u-net: A multi-scale neural network for end-to-end audio source separation
D. Stoller, S. Ewert, and S. Dixon · 2018
Later among the works it cites.
N. Takahashi, N. Goswami, and Y. Mitsufuji · 2018
Later among the works it cites.
Gradnorm : Gradient normalization for adaptive loss balancing in deep multitask networks
Z. Chao, V. Badrinarayanan, C.-Y. Lee, and A. Rabinovich · 2018
Later among the works it cites.
Jointly detecting and separating singing voice: A multi-task approach
D. Stoller, S. Ewert, and S. Dixon · 2018
Later among the works it cites.