Learning Where to Split: Dynamic Band Splitting for Audio Source Separation
Audio source separation models must preserve fine spectral structure while keeping the cost of the separator tractable. Band-split architectures reduce this cost by manually partitioning the spectrum into predefined frequency bands and encoding each band as a token, but the same boundaries are used for every mixture. Because informative spectral structure varies with source content, fixed boundaries can merge discriminative components or spend tokens where little resolution is needed. We introduce Dynamic Band Splitting (DBS), an end-to-end framework that adapts boundary locations and band widths to each mixture under a fixed band-token budget. DBS predicts content-conditioned boundary score
| Authors | Bingzhe Zhang, Kai Li, Xiaolin Hu |
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| Primary category | |
| Published | 10 October 2026 |
| Last updated at source | — |
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