English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We propose a method to generate audio adversarial examples that can attack astate-of-the-art speech recognition model in the physical world. Previous workassumes that generated adversarial examples are directly fed to the recognitionmodel, and is not able to perform such a physical attack because ofreverberation and noise from playback environments. In contrast, our methodobtains robust adversarial examples by simulating transformations caused byplayback or recording in the physical world and incorporating thetransformations into the generation process. Evaluation and a listeningexperiment demonstrated that our adversarial examples are able to attackwithout being noticed by humans. This result suggests that audio adversarialexamples generated by the proposed method may become a real threat.

Robust Audio Adversarial Example for a Physical Attack