2025/07/30 by Lin, Guan-Ting, Kuan, Shih-Yun Shan, Wang, Qirui +4 · 12 citations
#Audio and Speech Processing (eess.AS) #FOS: Electrical engineering #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2507.23159
While full-duplex speech agents promise natural, low-latency human-machine interaction by concurrently processing input and output speech, overlap management remains under-evaluated. We introduce Full-Duplex-Bench v1.5, a modular, fully automated benchmark that simulates four overlap scenarios: user interruption, listener backchannel, side conversation, and ambient speech. Our framework supports both open-sourced and commercial models, offering a comprehensive, extensible metric suite -- categorical dialogue behaviors, stop and response latency, prosodic adaptation, and perceived speech quality -- that can be tailored to application-specific criteria. Benchmarking five state-of-the-art agents reveals two principal strategies: repair-first rapid yielding versus continuity-first sustained flow, and highlights scenario-dependent performance trends. The open-sourced design enables seamless extension with new audio assets, languages, and deployment contexts, empowering practitioners to customize and accelerate the evaluation of robust full-duplex speech systems.