Musical Source Separation of Brazilian Percussion
Abstract
Musical source separation (MSS) has recently seen a big breakthrough in separating instruments from a mixture in the context of Western music, but research on non-Western instruments is still limited due to a lack of data. In this demo, we use an existing dataset of Brazilian sama percussion to create artificial mixtures for training a U-Net model to separate the surdo drum, a traditional instrument in samba. Despite limited training data, the model effectively isolates the surdo, given the drum's repetitive patterns and its characteristic low-pitched timbre. These results suggest that MSS systems can be successfully harnessed to work in more culturally-inclusive scenarios without the need of collecting extensive amounts of data.
Keywords
Cite
@article{arxiv.2503.04995,
title = {Musical Source Separation of Brazilian Percussion},
author = {Richa Namballa and Giovana Morais and Magdalena Fuentes},
journal= {arXiv preprint arXiv:2503.04995},
year = {2025}
}
Comments
2 pages + references, 1 figure, 1 table, Extended Abstracts for the Late-Breaking Demo Session of the 25th International Society for Music Information Retrieval Conference