Real-Time Interactive Music Generation via Data-Free Streaming Consistency Distillation
Interactive music and live performance relies on real-time human expression, but modern generative music AI remains largely absent from this domain due to its prohibitive inference latency and offline rendering paradigm. To provide pioneer musicians with a novel medium for interactive composition, we should fundamentally change these static models into dynamic, playable instruments. In this paper, we propose a framework that bridges this gap. To achieve the low latency required for live interaction without sacrificing structural coherence, we formulate distillation within a streaming autoregressive latent space. Our approach gets rid of the need for expensive paired audio-latent datasets ...
| Authors | Baisen Wang, Chenxi Bao, Qisong Han |
|---|---|
| Primary category | cs.SD |
| Published | 23 June 2026 |
| Last updated at source | 23 June 2026 |
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