3 papers
cs.SD2026
WeDefense: A Toolkit to Defend Against Fake Audio
Lin Zhang, Johan Rohdin, Xin Wang +8
The advances in generative AI have enabled the creation of synthetic audio which is perceptually indistinguishable from real, genuine audio. Although this stellar progress enables…
eess.AS2024
Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio
Lin Zhang, Xin Wang, Erica Cooper +4
This paper defines Spoof Diarization as a novel task in the Partial Spoof (PS) scenario. It aims to determine what spoofed when, which includes not only locating spoof regions but…
cs.SD2024
Do End-to-End Neural Diarization Attractors Need to Encode Speaker Characteristic Information?
Lin Zhang, Themos Stafylakis, Federico Landini +3
In this paper, we apply the variational information bottleneck approach to end-to-end neural diarization with encoder-decoder attractors (EEND-EDA). This allows us to investigate w…