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Adversarial Example Attacks against ASR Systems: An Overview

  • Xiao Zhang
  • , Hao Tan
  • , Xuan Huang
  • , Denghui Zhang
  • , Keke Tang
  • , Zhaoquan Gu
  • Guangzhou University
  • Peng Cheng Laboratory
  • Ministry of Industry and Information Technology
  • Laboratory of Miit for Intelligent Products Testing and Reliability
  • National University of Defense Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the development of hardware and algorithms, ASR(Automatic Speech Recognition) systems evolve a lot. As The models get simpler, the difficulty of development and deployment become easier, ASR systems are getting closer to our life. On the one hand, we often use APPs or APIs of ASR to generate subtitles and record meetings. On the other hand, smart speaker and self-driving car rely on ASR systems to control AIoT devices. In past few years, there are a lot of works on adversarial examples attacks against ASR systems. By adding a small perturbation to the waveforms, the recognition results make a big difference. In this paper, we describe the development of ASR system, different assumptions of attacks, and how to evaluate these attacks. Next, we introduce the current works on adversarial examples attacks from two attack assumptions: white-box attack and black-box attack. Different from other surveys, we pay more attention to which layer they perturb waveforms in ASR system, the relationship between these attacks, and their implementation methods. We focus on the effect of their works.

Original languageEnglish
Title of host publicationProceedings - 2022 7th IEEE International Conference on Data Science in Cyberspace, DSC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages470-477
Number of pages8
ISBN (Electronic)9781665474801
DOIs
StatePublished - 2022
Externally publishedYes
Event7th IEEE International Conference on Data Science in Cyberspace, DSC 2022 - Guilin, China
Duration: 11 Jul 202213 Jul 2022

Publication series

NameProceedings - 2022 7th IEEE International Conference on Data Science in Cyberspace, DSC 2022

Conference

Conference7th IEEE International Conference on Data Science in Cyberspace, DSC 2022
Country/TerritoryChina
CityGuilin
Period11/07/2213/07/22

Keywords

  • AI security
  • ASR
  • adversarial attacks
  • deep learning

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