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A Training-Efficient Transformer-Based Anti-Spoofing Network for Logical Access in ASVspoof 5
arXiv:2606.02980v1 Announce Type: new Abstract: Synthetic and manipulated speech can reduce the reliability of automatic speaker verification systems, so anti-spoofing methods need to be both accurate and efficient in training and inference. This paper focuses on the ASVspoof 5 Track 1 closed condition, where standard cross-entropy training may not give enough attention to hard trials and is not directly aligned with ranking- and threshold-based evaluation metrics. We propose TFPARN, a...