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README.md
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**MeanFlowSE** is a conditional generative approach to speech enhancement that learns average velocities over short time spans and performs enhancement in a single step. Instead of rolling out a long ODE trajectory, it applies one backward-in-time displacement directly in the complex STFT domain, delivering competitive quality at a fraction of the compute and latency. The model is trained end-to-end with a local JVP-based objective and remains consistent with conditional flow matching on the diagonal—no teacher models, schedulers, or distillation required. In practice, 1-NFE inference makes real-time deployment on standard hardware straightforward.
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* 🎧 **Demo**: demo page coming soon.
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**MeanFlowSE** is a conditional generative approach to speech enhancement that learns average velocities over short time spans and performs enhancement in a single step. Instead of rolling out a long ODE trajectory, it applies one backward-in-time displacement directly in the complex STFT domain, delivering competitive quality at a fraction of the compute and latency. The model is trained end-to-end with a local JVP-based objective and remains consistent with conditional flow matching on the diagonal—no teacher models, schedulers, or distillation required. In practice, 1-NFE inference makes real-time deployment on standard hardware straightforward.
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* 🎧 **Demo**: demo page coming soon.
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