ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake detection solutions. A significant change from previous challenge editions is a new crowdsourced database collected from a substantially greater number of speakers under diverse recording conditions, and a mix of cutting-edge and legacy generative speech technology. With the new database described elsewhere, we provide in this paper an overview of the ASVspoof 5 challenge results for the submissions of 53 participating teams. While many solutions perform well, performance degrades under adversarial attacks and the application of neural encoding/compression schemes. Together with a review of post-challenge results, we also report a study of calibration in addition to other principal challenges and outline a road-map for the future of ASVspoof.

翻译：ASVspoof 5是系列挑战赛的第五版，旨在推动语音欺骗与深度伪造检测解决方案的研究。与往届挑战赛相比，本次显著变化在于采用全新的众包数据库——该数据库从更大量的说话人、多样化的录制条件以及前沿与经典生成式语音技术的混合中采集。基于另文描述的新数据库，本文概述了ASVspoof 5挑战赛中53支参赛队伍的提交结果。尽管许多解决方案表现良好，但性能在对抗攻击以及神经编码/压缩方案的应用下有所下降。结合对赛后结果的分析，本文还报告了校准研究及其他主要挑战，并勾勒出ASVspoof未来的发展路线图。