EchoChain: A Full-Duplex Benchmark for State-Update Reasoning Under Interruptions
Smit Nautambhai Modi, Gandharv Mahajan, Marc Wetter, Randall Welles

TL;DR
EchoChain is a benchmark designed to evaluate how well voice assistants update their task state during mid-speech interruptions, revealing significant room for improvement in real-time state reasoning.
Contribution
It introduces a controlled, scenario-driven benchmark for assessing full-duplex state-update reasoning under interruptions, identifying common failure patterns.
Findings
Total failures decrease by 40.2% with half-duplex control.
No evaluated model exceeds 50% pass rate.
Many errors stem from state-update reasoning rather than task difficulty.
Abstract
Real-time voice assistants must revise task state when users interrupt mid-response, but existing spoken-dialog benchmarks largely evaluate turn-based interaction and miss this failure mode. We introduce EchoChain, a controlled benchmark for evaluating full-duplex state-update reasoning under mid-speech interruptions. EchoChain identifies three recurring failure patterns in post-interruption continuations: contextual inertia, interruption amnesia, and objective displacement. The benchmark generates scenario-driven conversations and injects interruptions at a standardized point relative to assistant speech onset, enabling controlled cross-model comparison. In a paired half-duplex control, total failures drop by 40.2% relative to interrupted runs, indicating that many errors are driven by state-update reasoning under interruption rather than task difficulty alone. Across evaluated…
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