DuplexCadence: Exact State and Execution from a Speech Model's Declared Timelines
Full-duplex speech models support streaming interaction that listens and speaks at the same time. Serving them is governed by a strict, repeating deadline: conversation advances on a one-second cadence, and every second of input must be turned into a second of speech before the next second arrives. Because stages within a session run in strict sequence, per-invocation overhead cannot be batched away. Profiling reveals that the autoregressive stages of a duplex second already fit within the period, whereas the token-to-audio synthesis tail is what causes overruns. This tail stage suffers from orchestration slack where the GPU is left waiting as thousands of tiny, regular operations are iss...
| Authors | Haixiao Gao, Yimin Zheng, Linyou Xiao et al. |
|---|---|
| Primary category | cs.AI |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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