Leveraging Domain Features for Detecting Adversarial Attacks Against Deep Speech Recognition in Noise. (arXiv:2211.01621v1 [eess.AS])

In recent years, significant progress has been made in deep model-based
automatic speech recognition (ASR), leading to its widespread deployment in the
real world. At the same time, adversarial attacks against deep ASR systems are
highly successful. Various methods have been proposed to defend ASR systems
from these attacks. However, existing classification based methods focus on the
design of deep learning models while lacking exploration of domain specific
features. This work leverages filter bank-based features to better capture the
characteristics …

adversarial attacks domain features recognition speech