On the potential of jointly-optimised solutions to spoofing attack detection and automatic speaker verification

TL;DR

This paper investigates the challenges and potential benefits of jointly optimizing spoofing detection and speaker verification systems, revealing that current approaches improve spoofing robustness but often degrade speaker verification performance.

Contribution

The study analyzes why joint optimization has not been successful in SASV and suggests strategies for better integration of the two tasks.

Findings

Joint optimization improves spoofing robustness.

Joint optimization can degrade speaker verification performance.

Progress depends on data collection from more speakers.

Abstract

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.