Precision-Varying Prediction (PVP): Robustifying ASR systems against adversarial attacks

ArXi:2603.22590v1 Announce Type: new With the increasing deployment of automated and agentic systems, ensuring the adversarial robustness of automatic speech recognition (ASR) models has become critical. We observe that changing the precision of an ASR model during inference reduces the likelihood of adversarial attacks succeeding. We take advantage of this fact to make the models robust by simple random sampling of the precision during prediction.