The Sound Demixing Challenge 2023 – Music Demixing Track

Author:

Fabbro GiorgioORCID,Uhlich StefanORCID,Lai Chieh-HsinORCID,Choi Woosung,Martínez-Ramírez Marco,Liao Weihsiang,Gadelha Igor,Ramos Geraldo,Hsu Eddie,Rodrigues Hugo,Stöter Fabian-Robert,Défossez Alexandre,Luo Yi,Yu Jianwei,Chakraborty Dipam,Mohanty SharadaORCID,Solovyev RomanORCID,Stempkovskiy AlexanderORCID,Habruseva TatianaORCID,Goswami NabarunORCID,Harada TatsuyaORCID,Kim Minseok,Hyung Lee JunORCID,Dong YuanliangORCID,Zhang XinranORCID,Liu JiafengORCID,Mitsufuji YukiORCID

Publisher

Ubiquity Press, Ltd.

Reference47 articles.

1. MedleyDB: A multitrack dataset for annotation-intensive MIR research,2014

2. A consolidated view of loss functions for supervised deep learningbased speech enhancement,2020

3. Learning with instance-dependent label noise: A sample sieve approach;arXiv preprint arXiv:2010.02347,2020

4. Investigating U-Nets with various intermediate blocks for spectrogram-based singing voice separation,2020

5. Hybrid spectrogram and waveform source separation,2021

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Jazz Trio Database: Automated Annotation of Jazz Piano Trio Recordings Processed Using Audio Source Separation;Transactions of the International Society for Music Information Retrieval;2024-08-27

2. Why Does Music Source Separation Benefit from Cacophony?;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

3. Music Source Separation With Band-Split Rope Transformer;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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