Speech-Hands: A voice agent that knows when to trust itself
What if a speech AI could pause and double-check its hearing when the sound gets messy? That’s the idea behind Speech-Hands, a new voice-agentic framework that teaches models to know when to trust themselves—and when to ask for help.
Instead of blindly mixing speech recognition with external audio perception, Speech-Hands adds a learnable self-reflection step. For every audio snippet, the agent explicitly decides: rely on its own transcription, or consult external candidates. This simple decision prevents noisy guesses from derailing the model and naturally extends from transcription to multiple-choice audio reasoning.
- On the OpenASR leaderboard, it cut word error rate by 12.1% across seven benchmarks.
- On audio question answering, it reached 77.37% accuracy with high F1, showing robust generalization.
Why it matters: by unifying perception and decision-making, Speech-Hands builds more reliable, resilient audio intelligence—for voice assistants, contact centers, and accessibility tools.
Paper: https://arxiv.org/abs/2601.09413v1
Paper: https://arxiv.org/abs/2601.09413v1
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