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Voice Processing Systems (VPSes), now widely deployed, have become deeply involved in people’s daily lives, helping drive the car, unlock the smartphone, make online purchases, etc. Unfortunately, recent research has shown that those systems based on deep neural networks are vulnerable to adversarial examples, which attract significant attention to VPS security. This review presents a detailed introduction to the background knowledge of adversarial attacks, including the generation of adversarial examples, psychoacoustic models, and evaluation indicators. Then we provide a concise introduction to defense methods against adversarial attacks. Finally, we propose a systematic classification of adversarial attacks and defense methods, with which we hope to provide a better understanding of the classification and structure for beginners in this field.

Adversarial Attack and Defense on Deep Neural Network-Based Voice Processing Systems: An Overview