arXiv Machine Learning By Weichuang Shao, Iman Yi Liao, Tomas Henrique Bode Maul, Tissa Chandesa

DHAuDS: A Dynamic and Heterogeneous Audio Benchmark for Test-Time Adaptation

Read the original on arXiv Machine Learning →

arXiv:2511. 18421v2 Announce Type: replace-cross Abstract: Existing Test-time Adaptation (TTA) studies rely heavily on static and homogeneous corruption protocols, such as ImageNet-C and CIFAR-10-C/100-C, leading to inconsistent evaluation settings and potentially inflated robustness estimates that are compared with real-world situations.

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Teffic-Audio: Tell Fact from Fiction

arXiv:2607. 28351v2 Announce Type: replace-cross Abstract: Speech deepfake detection has expanded in scope with increasingly heterogeneous spoofing mechanisms, including speech synthesis, voice conversion, vocoder reconstruction, and neural-codec resynthesis.

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