Author

Wenjie Li

View on Semantic Scholar

1 paper indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Jul 2026

CAFAD: common acoustic features for adversarial audio detection

CAFAD is proposed, a plug-and-play detection framework that combines multi-domain acoustic feature fusion and temporal pyramid matching for variable-length adversarial audio detection that achieves an average detection accuracy of 99.25%, with a false positive rate of 1.00% on benign samples.

Wenjie Li, Pengyu Wei, Xuejing Yuan et al. · Cybersecurity · 0 citations