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MECT, a speaker verification model that integrates the Mixture-of-Experts (MoE) mechanism into a CNN-Transformer backbone with optimized block structure and stacking scheme, achieves state-of-the-art performance on VoxCeleb1 and delivers strong results on CN-Celeb, demonstrating its effectiveness across diverse datasets.
Winning systems in the AT-ADD challenge achieved over 90% accuracy in detecting all types of audio deepfakes, showcasing the potential of innovative detection strategies.
