DuplexSLA introduces a three-channel full-duplex architecture that synchronizes continuous user audio, discrete assistant audio, and rate-limited textual actions inside a single backbone for native turn-taking and in-conversation tool use.
Talking turns: Benchmarking audio foundation models on turn-taking dynamics
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SHREC is a new benchmark dataset of embodied human-robot conversations that shows substantial performance gaps in state-of-the-art foundation models on tasks involving social error detection and rationale generation.
TurnNat introduces a likelihood-based automatic evaluation method for turn-taking naturalness in dyadic spoken dialogues using a causal prediction model and a human-validated perturbation benchmark.
ModeratorLM conditions a streaming speech LLM on assigned roles for adaptive turn-taking in multi-party settings, reporting over 40% higher precision and 70% higher recall than non-role baselines on real meetings and a new synthetic dataset.
A survey of Large Audio Language Models that establishes a taxonomy of trustworthiness vulnerabilities and proposes a Defense-in-Depth roadmap for audio intelligence.
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Social Human Robot Embodied Conversation (SHREC) Dataset: Benchmarking Foundational Models' Social Reasoning
SHREC is a new benchmark dataset of embodied human-robot conversations that shows substantial performance gaps in state-of-the-art foundation models on tasks involving social error detection and rationale generation.