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AT-ADD: A Benchmark and Challenge for Robust and All-Type Audio Deepfake Detection
Recent audio generation models can synthesize high-fidelity speech, environmental sound, singing voice, and music, creating new risks for multimedia trust. Existing audio deepfake detection (ADD) benchmarks remain predominantly speech-centric and often under-represent realistic channel variation and
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