Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition

arXiv: Audio and Speech Processing, 2019.

Cited by: 77|Bibtex|Views178
EI
Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Adversarial examples are inputs to machine learning models designed by an adversary to cause an incorrect output. So far, adversarial examples have been studied most extensively in the image domain. In this domain, adversarial examples can be constructed by imperceptibly modifying images to cause misclassification, and are practical in th...More

Code:

Data:

Full Text
Your rating :
0

 

Tags
Comments