# Semantic-Aware Interruption Detection in Spoken Dialogue Systems: Benchmark, Metric, and Model Source: [Semantic-Aware Interruption Detection in Spoken Dialogue Systems: Benchmark, Metric, and Model]() Collection index: [llms.txt]() Data updated: 2026-03-27T05:00:04.195Z Authors: Kangxiang Xia, Bingshen Mu, Xian Shi, Jin Xu, Lei Xie Published: 2026-03-25T10:11:33.000Z ## Abstract Achieving natural full-duplex interaction in spoken dialogue systems (SDS) remains a challenge due to the difficulty of accurately detecting user interruptions. Current solutions are polarized between "trigger-happy" VAD-based methods that misinterpret backchannels and robust end-to-end models that exhibit unacceptable response delays. Moreover, the absence of real-world benchmarks and holistic metrics hinders progress in the field. This paper presents a comprehensive frame-work to overcome these limitations. We first introduce SID-Bench, the first benchmark for semantic-aware interruption detection built entirely from real-world human dialogues. To provide a rigorous assessment of the responsiveness-robustness trade-off, we propose the Average Penalty Time (APT) metric, which assigns a temporal cost to both false alarms and late responses. Building on this framework, we design an LLM-based detection model optimized through a novel training paradigm to capture subtle semantic cues of intent. Experimental results show that our model significantly outperforms mainstream baselines, achieving a nearly threefold reduction in APT. By successfully resolving the long-standing tension between speed and stability, our work establishes a new state-of-the-art for intelligent interruption handling in SDS. To facilitate future research, SID-Bench and the associated code are available at: https://github.com/xkx-hub/SID-bench. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Speech Interruption Handling on SID-Bench Noise Silence 1.0](): Speech Interruption Handling; SID-Bench Noise Silence 1.0; FIR Score: 2.6. - [Speech Interruption Handling on SID-Bench English 1.0](): Speech Interruption Handling; SID-Bench English 1.0; IRL: 0.444. - [Speech Interruption Handling on SID-Bench Average 1.0 (All combined)](): Speech Interruption Handling; SID-Bench Average 1.0 (All combined); IRL: 0.389. - [Speech Interruption Handling on SID-Bench Chinese 1.0](): Speech Interruption Handling; SID-Bench Chinese 1.0; IRL: 0.338. ## Original sources and implementation [Original paper]() [PDF]()