这篇论文揭示了语音识别错误如何导致具身AI执行危险指令，并提出了评估方法。
研究表明语音识别(ASR)错误可能导致具身AI(EAI)模型接受并执行有害指令。研究人员通过模拟ASR错误并结合SafeAgentBench和POEX基准测试评估了不同错误对具身AI安全的影响。某些错误保留了语义结构但增加了有害歧义，而另一些错误则削弱了模型的拒绝行为，允许生成和执行不安全计划。自动纠正ASR错误在某些情况下可以降低风险，但并非总是有效。
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 safety. We simulate ASR errors and combine them with existing safety benchmarks (SafeAgentBench and POEX) to evaluate how different errors affect embodied AI safety. We find that some of them preserve semantic structure but increase harmful ambiguity, while others weaken the model refusal behaviour and allow unsafe plans to be generated and executed. We show that in some cases automatic correction of ASR errors can reduce the risk, but this is not always effective. Overall, we show that ASR errors lead to significant safety risks for embodied AI.