NVIDIA paper: routing voice-agent tool calls to a text LLM lifts recall above 92%
omarsar0 · x · 2026-09-20
A new NVIDIA research paper gives full-duplex speech models tool-calling ability by routing decisions out of the speech pipeline:
- Commercial duplex voice models complete only 31-51% of grounded customer-service tasks under clean conditions, while text agents like GPT-5 hit 85% on the same tasks.
- The fix: the duplex frontend learns to emit a delegation token, forwards streaming transcripts to a text backend LLM for the tool call, and receives results via a lightweight prefill-and-repeat mechanism before streaming TTS speaks them.
- Results: 92.0-97.2% tool-call recall, 81.2% accuracy at rejecting irrelevant calls, with turn-taking, streaming ASR WER, and spoken-language intelligence unchanged.
Related event: NVIDIA Open-Sources Full-Duplex VoiceChat with Tool Calling(2 posts)→
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