We investigate whether automatic speech recognition (ASR) errors in user input can lead to unsafe outputs from Embodied AI (EAI) models. We find that ASR errors can lead to harmful instructions being accepted and executed by EAI models, thereby reducing safet...
VQV Signal
ROBOTS & HARDWARE
SOURCE-BACKED
TECHNICAL
When Robots Mishear Us: Mapping the Safety Risks of Voice-Controlled Embodied AI
We investigate whether automatic speech recognition (ASR) errors in user input can lead to unsafe outputs from Embodied AI (EAI) models. We find that ASR errors can lead to harmful instructions being accepted and executed by EAI models, thereby reducing safet...
We investigate whether automatic speech recognition (ASR) errors in user input can lead to unsafe outputs from Embodied AI (EAI) models. We find that ASR errors can lead to harmful instructions being accepted and executed by EAI models, thereby reducing safety. We simulate ASR errors and combine them with existing...
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Signal Strength 95%
Technical label SOURCE-BACKED
Public Interest 32
Category ROBOTS & HARDWARE
Reader Depth TECHNICAL
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
Recognizable Entity Score 0
Practical Impact Score 0
Novelty Interest Score 72
Consequence Score 46
Curiosity Score 64
Shareability Score 41
Topics
VQV surfaced this signal because it is recent, relevant to Robotics, connected to arXiv.
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