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Phonemic Adversarial Attack against Audio Recognition in Real World. (arXiv:2211.10661v1 [cs.SD])
Nov. 22, 2022, 2:20 a.m. | Jiakai Wang, Zhendong Chen, Zixin Yin, Qinghong Yang, Xianglong Liu
cs.CR updates on arXiv.org arxiv.org
Recently, adversarial attacks for audio recognition have attracted much
attention. However, most of the existing studies mainly rely on the
coarse-grain audio features at the instance level to generate adversarial
noises, which leads to expensive generation time costs and weak universal
attacking ability. Motivated by the observations that all audio speech consists
of fundamental phonemes, this paper proposes a phonemic adversarial tack (PAT)
paradigm, which attacks the fine-grain audio features at the phoneme level
commonly shared across audio instances, to …
More from arxiv.org / cs.CR updates on arXiv.org
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