Adversarial Examples for Automatic Speech Recognition : Attacks and Countermeasures

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

36 Scopus Citations
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Author(s)

  • Xingcan Shang
  • Zhan Qin
  • Minghui Li
  • Qian Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number8809565
Pages (from-to)120-126
Journal / PublicationIEEE Communications Magazine
Volume57
Issue number10
Online published21 Aug 2019
Publication statusPublished - Oct 2019

Abstract

Speech is a common and effective approach for communication between humans and modern mobile devices such as smartphones or home hubs. The remarkable advances in computing and networking have popularized automatic speech recognition (ASR) systems, which can interpret received speech signals on mobile devices and enable us to remotely control and interact with those devices. Despite promising development, audio adversarial examples, a new kind of attack on advanced ASR systems, are found to be extremely effective in imitating human speech while fooling mobile devices to produce incorrect commands. In this article, we provide a systematic survey of audio adversarial examples in the literature. We first present an overview of the architecture of ASR systems and outline the basic attack philosophy. Followed by a brief introduction of the state-of-the-art solutions to audio adversarial examples, a comprehensive comparison is presented. Finally, after discussing existing countermeasures to defend ASR, we highlight several promising future research directions and challenges on constructing more robust and practical audio adversarial examples.

Citation Format(s)

Adversarial Examples for Automatic Speech Recognition: Attacks and Countermeasures. / Hu, Shengshan; Shang, Xingcan; Qin, Zhan et al.
In: IEEE Communications Magazine, Vol. 57, No. 10, 8809565, 10.2019, p. 120-126.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review