Deep Learning Based Source Separation Applied To Choir Ensembles

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P. Chandna, M. Miron, J. Janer, and E. Gómez", “Monoaural Audio Source Separation Using Deep Convolutional Neural Networks,” in International Conference on Latent Variable Analysis and Signal Separation , 2017, pp. 258–266

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Z. Rafii, A. Liutkus, F.-R. Stöter, S. I. Mimilakis, and R. Bittner, “The MUSDB18 corpus for music separation,” December 2017. [Online]. Available: https://doi.org/10.5281/zenodo.1117372

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A. Jansson, E. Humphrey, N. Montecchio, R. Bittner, A. Kumar, and T. Weyde, “Singing Voice Separation with Deep U-Net Convolutional Networks,” in Proceedings of the International Society for Music Information Retrieval Conference (ISMIR) , 2017

2017

Cited alongside, same era.

R. M. Bittner, B. McFee, J. Salamon, P. Li, and J. P. Bello, “Deep Salience Representations for F0 Estimation in Polyphonic Music,” in Proceedings of the International Society for Music Information Retrieval Conference, (ISMIR) , 2017

2017

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D. Stoller, S. Ewert, and S. Dixon, “Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation,” in Proceedings of the International Society for Music Information Retrieval Conference (ISMIR) , 2018

2018

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G. Meseguer-Brocal and G. Peeters, “Conditioned u-net: Introducing a control mechanism in the u-net for multiple source separations.” November 2019

2019

Later among the works it cites.

H. Cuesta, E. Gómez, and P. Chandna, “A Framework for Multi-f0 Modeling in SATB Choir Recordings,” in Proceedings of the Sound and Music Computing (SMC) Conference , Málaga (Spain), April 2019

2019

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M. Silvestri, M. Lombardi, and M. Milano, “Injecting domain knowledge in neural networks: a controlled experiment on a constrained problem,” ArXiv , vol. abs/2002.10742, 2020

Original

2020

Closest in time.

H. Cuesta, B. McFee, and E. Gómez, “Multiple F0 Estimation in Vocal Ensembles using Convolutional Neural Networks,” in Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR) , Montreal, Canada (Virtual), 2020

2020

Closest in time.