论文标题
关于欺骗攻击检测和自动扬声器验证的共同解决方案的潜力
On the potential of jointly-optimised solutions to spoofing attack detection and automatic speaker verification
论文作者
论文摘要
欺骗意识到的说话者验证（SASV）挑战旨在促进对共同优化的解决方案的研究，以完成传统上分开的欺骗检测和说话者验证的任务。共同优化的系统有可能在协同作用中运行，以便更好地执行可靠扬声器验证的单一任务。但是，共同优化了SASV 2022的23项提交。因此，我们试图确定为什么分别优化的子系统表现最佳，或者为什么关节优化不成功。本文报道的实验表明，关节优化成功地改善了欺骗的鲁棒性，但它会降低说话者验证性能。研究结果表明，应共同优化欺骗检测和说话者验证子系统，以反映每个子系统提供的信息的差异与对方提供的信息互补。进度也可能取决于来自大量说话者的数据收集。
The spoofing-aware speaker verification (SASV) challenge was designed to promote the study of jointly-optimised solutions to accomplish the traditionally separately-optimised tasks of spoofing detection and speaker verification. Jointly-optimised systems have the potential to operate in synergy as a better performing solution to the single task of reliable speaker verification. However, none of the 23 submissions to SASV 2022 are jointly optimised. We have hence sought to determine why separately-optimised sub-systems perform best or why joint optimisation was not successful. Experiments reported in this paper show that joint optimisation is successful in improving robustness to spoofing but that it degrades speaker verification performance. The findings suggest that spoofing detection and speaker verification sub-systems should be optimised jointly in a manner which reflects the differences in how information provided by each sub-system is complementary to that provided by the other. Progress will also likely depend upon the collection of data from a larger number of speakers.
