"Hello, It's Me": Deep Learning-based Speech Synthesis Attacks in the Real World
Emily Wenger
Max Bronckers
Christian Cianfarani
Jenna Cryan
Angela Sha
Haitao Zheng
Ben Y. Zhao
Proceedings of the 28th ACM Conference on Computer and Communications Security (CCS)
[Full Text in PDF Format, 632KB]
Paper Abstract
Advances in deep learning have introduced a new wave of voice synthesis
tools, capable of producing audio that sounds as if spoken by a target
speaker. If successful, such tools in the wrong hands will enable a
range of powerful attacks against both humans and software systems (aka
machines). This paper documents efforts and findings from a
comprehensive experimental study on the impact of deep-learning based
speech synthesis attacks on both human listeners and machines such as
speaker recognition and voice-signin systems. We find that both humans
and machines can be reliably fooled by synthetic speech, and that
existing defenses against synthesized speech fall short. These findings
highlight the need to raise awareness and develop new protections
against synthetic speech for both humans and machines.