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Multiparty Bench is introduced, the first benchmark specifically designed to objectively evaluate conversational speech systems as active participants within multi-party contexts and assesses agent behavior along two primary dimensions: turn-taking awareness and response appropriateness.
This work refine warm-initialized LLM-based ASR models by leveraging their own pre-adaptation base LLMs by leveraging their own pre-adaptation base LLMs, focusing on LoRA-adapted settings where the base LLM is preserved.
TurnBench, a multi-domain benchmark that pairs a 30-hour, hand-labeled corpus of dyadic human conversation with a standardized evaluation protocol for end-of-turn and interruption detection, finds end-of-turn recall stable across types, while interruption false positives are strongly type-dependent and concentrated in...
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