对比两个语音伪造检测挑战赛，发现新数据集更难辨识真声与伪造声。
ASVspoof2019 vs. ASVspoof5: Assessment and Comparison
- 比较ASVspoof2019与ASVspoof5的数据设置差异
- 新数据集使真实语音和伪造语音都更难区分
- 适合研究语音验证系统鲁棒性的学者参考
ASVspoof挑战旨在推动对语音伪造攻击的理解，并促进鲁棒反欺骗系统的开发。这些挑战提供标准化数据库，用于评估和比较抗欺骗的自动说话人验证方案。与ASVspoof2019相比，ASVspoof5在数据库设置上引入了变化：2019年仅在测试集的伪造攻击中存在不匹配条件，而5版则在真实语音和伪造语音统计上均引入不匹配。本文分析了这种不匹配的影响，进行了两数据库内部及之间的定性和定量比较。结果表明，真实语音与伪造语音的界限更加模糊，且在ASVspoof5中，不仅攻击更具挑战性，真实语音也更趋近于伪造语音的表现，整体难度显著提升。
原文摘要 · Abstract (English)
ASVspoof challenges are designed to advance the understanding of spoofing speech attacks and encourage the development of robust countermeasure systems. These challenges provide a standardized database for assessing and comparing spoofing-robust automatic speaker verification solutions. The ASVspoof5 challenge introduces a shift in database conditions compared to ASVspoof2019. While ASVspoof2019 has mismatched conditions only in spoofing attacks in the evaluation set, ASVspoof5 incorporates mismatches in both bona fide and spoofed speech statistics. This paper examines the impact of these mismatches, presenting qualitative and quantitative comparisons within and between the two databases. We show the increased difficulty for genuine and spoofed speech and demonstrate that in ASVspoof5, not only are the attacks more challenging, but the genuine speech also shifts toward spoofed speech compared to ASVspoof2019.
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