Abstract
Adversarial examples are inputs with slight intentional perturbations that lead to incorrect predictions of deep neural networks; they also threaten automatic speech recognition systems. This study proposes a method to uncover such threats in practical environments, focusing on hard‐label black‐box settings. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.