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cs.SD2026
MECT: Mixture of Experts with CNN-Transformer Network for Speaker verification
Yu Zheng, Jinghan Peng, ChangHao Zhang +2
In this paper, we propose MECT, a speaker verification model that integrates the Mixture-of-Experts (MoE) mechanism into a CNN-Transformer backbone with optimized block structure a…
cs.SD2026
AT-ADD: A Benchmark and Challenge for Robust and All-Type Audio Deepfake Detection
Yuankun Xie, Haonan Cheng, Jiayi Zhou +12
Recent audio generation models can synthesize high-fidelity speech, environmental sound, singing voice, and music, creating new risks for multimedia trust. Existing audio deepfake…
cs.SD2026
AT-ADD: All-Type Audio Deepfake Detection Challenge Summary
Yuankun Xie, Haonan Cheng, Jiayi Zhou +11
This paper summarizes the ACM Multimedia 2026 AT-ADD Grand Challenge on all-type audio deepfake detection. AT-ADD contains two tracks: robust speech deepfake detection under realis…