2 citations · 3 across the 3 of their papers we have counts for
3 papers
eess.AS2024
Why does music source separation benefit from cacophony?
Chang-Bin Jeon, Gordon Wichern, François G. Germain +1
In music source separation, a standard training data augmentation procedure is to create new training samples by randomly combining instrument stems from different songs. These ran…
eess.AS2023★ 2 cited
Self-refining of Pseudo Labels for Music Source Separation with Noisy Labeled Data
Junghyun Koo, Yunkee Chae, Chang-Bin Jeon +1
Music source separation (MSS) faces challenges due to the limited availability of correctly-labeled individual instrument tracks. With the push to acquire larger datasets to improv…
cs.SD2022★ 1 cited
Towards robust music source separation on loud commercial music
Chang-Bin Jeon, Kyogu Lee
Nowadays, commercial music has extreme loudness and heavily compressed dynamic range compared to the past. Yet, in music source separation, these characteristics have not been thor…