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