Pith. sign in

REVIEW 1 cited by

"Hello, It's Me": Deep Learning-based Speech Synthesis Attacks in the Real World

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2109.09598 v1 pith:3YE3LZUU submitted 2021-09-20 cs.CR cs.AIcs.SDeess.AS

classification cs.CRcs.AIcs.SDeess.AS
keywords speechmachinesattackshumanssynthesisdeepfindingsspeaker
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original 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.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. XAttnMark: Learning Robust Audio Watermarking with Cross-Attention

    cs.SD 2025-02 unverdicted novelty 5.0 of 10

    XAttnMark is a new neural audio watermarking method using partial parameter sharing, cross-attention for message retrieval, temporal conditioning, and a psychoacoustic TF masking loss that reports state-of-the-art det...

Pith tools