most citedA Survey on Speech Deepfake Detection

56 citations · 64 across the 5 of their papers we have counts for

collaborators
Showing cs.SDShow all

5 papers · 1 filter

cs.SD2025

HQ-MPSD: A Multilingual Artifact-Controlled Benchmark for Partial Deepfake Speech Detection

Menglu Li, Majd Alber, Ramtin Asgarianamiri +2

Detecting partial deepfake speech is challenging because manipulations occur only in short regions while the surrounding audio remains authentic. However, existing detection method…

cs.SD2025

Frame-level Temporal Difference Learning for Partial Deepfake Speech Detection

Menglu Li, Xiao-Ping Zhang, Lian Zhao

Detecting partial deepfake speech is essential due to its potential for subtle misinformation. However, existing methods depend on costly frame-level annotations during training, l…

cs.SD2025

Beyond Identity: A Generalizable Approach for Deepfake Audio Detection

Yasaman Ahmadiadli, Xiao-Ping Zhang, Naimul Khan

Deepfake audio presents a growing threat to digital security, due to its potential for social engineering, fraud, and identity misuse. However, existing detection models suffer fro…

cs.SD2024★ 8 cited

Interpretable Temporal Class Activation Representation for Audio Spoofing Detection

Menglu Li, Xiao-Ping Zhang

Explaining the decisions made by audio spoofing detection models is crucial for fostering trust in detection outcomes. However, current research on the interpretability of detectio…

cs.SD2024★ 56 cited

A Survey on Speech Deepfake Detection

Menglu Li, Yasaman Ahmadiadli, Xiao-Ping Zhang

The availability of smart devices leads to an exponential increase in multimedia content. However, advancements in deep learning have also enabled the creation of highly sophistica…