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% bibtex
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@inproceedings{SISEC18,
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author = {{St{\"o}ter}, Fabian-Robert and {Liutkus}, Antoine and {Ito}, Nobutaka},
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title = {The 2018 Signal Separation Evaluation Campaign},
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year = {2018},
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booktitle = {Latent Variable Analysis and Signal Separation. {LVA}/{ICA}},
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vol={10891},
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doi = {10.1007/978-3-319-93764-9_28},
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publisher = { Springer, Cham}
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}
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@misc{spleeter2019,
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title={Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models},
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author={Romain Hennequin and Anis Khlif and Felix Voituret and Manuel Moussallam},
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howpublished={Late-Breaking/Demo ISMIR 2019},
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month={November},
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note={Deezer Research},
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year={2019}
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}
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@inproceedings{unet2017,
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title={Singing voice separation with deep U-Net convolutional networks},
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author={Jansson, Andreas and Humphrey, Eric J. and Montecchio, Nicola and Bittner, Rachel and Kumar, Aparna and Weyde, Tillman},
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booktitle={Proceedings of the International Society for Music Information Retrieval Conference (ISMIR)},
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pages={323--332},
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year={2017}
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}
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@inproceedings{deezerICASSP2019,
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author={Laure {Pr\'etet} and Romain {Hennequin} and Jimena {Royo-Letelier} and Andrea {Vaglio}},
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booktitle={ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
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title={Singing Voice Separation: A Study on Training Data},
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year={2019},
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volume={},
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number={},
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pages={506-510},
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keywords={feature extraction;source separation;speech processing;supervised training;separation quality;data augmentation;singing voice separation systems;singing voice separation algorithms;separation diversity;source separation;supervised learning;training data;data augmentation},
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doi={10.1109/ICASSP.2019.8683555},
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ISSN={},
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month={May},}
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@misc{Norbert,
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author = {Antoine Liutkus and
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Fabian-Robert St{\"o}ter},
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title = {sigsep/norbert: First official Norbert release},
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month = jul,
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year = 2019,
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doi = {10.5281/zenodo.3269749},
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url = {https://doi.org/10.5281/zenodo.3269749}
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}
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@ARTICLE{separation_metrics,
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author={Emmanuel {Vincent} and Remi {Gribonval} and Cedric {Fevotte}},
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journal={IEEE Transactions on Audio, Speech, and Language Processing},
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title={Performance measurement in blind audio source separation},
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year={2006},
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volume={14},
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number={4},
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pages={1462-1469},
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keywords={audio signal processing;blind source separation;distortion;time-varying filters;blind audio source separation;distortions;time-invariant gains;time-varying filters;source estimation;interference;additive noise;algorithmic artifacts;Source separation;Data mining;Filters;Additive noise;Microphones;Distortion measurement;Energy measurement;Independent component analysis;Interference;Image analysis;Audio source separation;evaluation;measure;performance;quality},
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doi={10.1109/TSA.2005.858005},
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ISSN={},
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month={July},}
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@misc{musdb18,
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author = {Rafii, Zafar and
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Liutkus, Antoine and
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Fabian-Robert St{\"o}ter and
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Mimilakis, Stylianos Ioannis and
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Bittner, Rachel},
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title = {The {MUSDB18} corpus for music separation},
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month = dec,
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year = 2017,
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doi = {10.5281/zenodo.1117372},
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url = {https://doi.org/10.5281/zenodo.1117372}
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}
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@misc{tensorflow2015-whitepaper,
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title={ {TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
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url={https://www.tensorflow.org/},
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note={Software available from tensorflow.org},
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author={
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Abadi, Mart{\'{\i}}n et al.},
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year={2015},
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}
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@article{2019arXiv190611139L,
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author = {{Lee}, Kyungyun and {Nam}, Juhan},
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title = "{Learning a Joint Embedding Space of Monophonic and Mixed Music Signals for Singing Voice}",
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journal = {arXiv e-prints},
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keywords = {Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing},
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year = "2019",
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month = "Jun",
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eid = {arXiv:1906.11139},
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pages = {arXiv:1906.11139},
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archivePrefix = {arXiv},
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eprint = {1906.11139},
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primaryClass = {cs.SD},
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adsurl = {https://ui.adsabs.harvard.edu/abs/2019arXiv190611139L},
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adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@article{Adam,
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author = {{Kingma}, Diederik P. and {Ba}, Jimmy},
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title = "{Adam: A Method for Stochastic Optimization}",
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journal = {arXiv e-prints},
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keywords = {Computer Science - Machine Learning},
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year = "2014",
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month = "Dec",
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eid = {arXiv:1412.6980},
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pages = {arXiv:1412.6980},
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archivePrefix = {arXiv},
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eprint = {1412.6980},
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primaryClass = {cs.LG},
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adsurl = {https://ui.adsabs.harvard.edu/abs/2014arXiv1412.6980K},
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adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@article{Open-Unmix,
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author={Fabian-Robert St\"{o}ter and Stefan Uhlich and Antoine Liutkus and Yuki Mitsufuji},
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title={Open-Unmix - A Reference Implementation for Music Source Separation},
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journal={Journal of Open Source Software},
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year=2019,
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doi = {10.21105/joss.01667},
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url = {https://doi.org/10.21105/joss.01667}
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}
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@misc{spleeter,
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author={Romain Hennequin and Anis Khlif and Felix Voituret and Manuel Moussallam},
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title={Spleeter},
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year=2019,
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url = {https://www.github.com/deezer/spleeter}
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}
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@misc{demucs,
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title={Music Source Separation in the Waveform Domain},
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author={Alexandre Défossez and Nicolas Usunier and Léon Bottou and Francis Bach},
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year={2019},
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eprint={1911.13254},
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archivePrefix={arXiv},
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primaryClass={cs.SD}
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}
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