The Costs of Reproducibility in Music Separation Research: a Replication of Band-Split RNN
Music source separation is the task of isolating the instrumental tracks from a music song. Despite its spectacular recent progress, the trend towards more complex architectures and training protocols exacerbates reproducibility issues. The band-split recurrent neural networks (BSRNN) model is promising in this regard, since it yields close to state-of-the-art results on public datasets, and requires reasonable resources for training. Unfortunately, it is not straightforward to reproduce since its full code is not available. In this paper, we attempt to replicate BSRNN as closely as possible to the original paper through extensive experiments, which allows us to conduct a critical reflect...
| Authors | Paul Magron, Romain Serizel, Constance Douwes |
|---|---|
| Primary category | cs.SD |
| Published | 10 March 2026 |
| Last updated at source | 10 March 2026 |
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