Iterative Audio Separation with Mixture Consistency via MIMO Model Extension
This paper proposes a general framework for stable and effective iterative audio separation with mixture consistency by extending source separation models to a multi-input multi-output (MIMO) configuration. In the field of audio separation, mixture consistency is an essential property for many applications that require accurate phase and timbral information of target sources. While iterative approaches such as diffusion models achieve perceptually superior results in speech enhancement or user-guided target source separation tasks, most existing methods focus on single-step separation with a single-input single-output (SISO) or single-input multi-output (SIMO) configuration through archit...
| Authors | Yukara Ikemiya, WeiHsiang Liao, Yuki Mitsufuji |
|---|---|
| Primary category | cs.SD |
| Published | 7 September 2026 |
| Last updated at source | 7 September 2026 |
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