  Automatic Speaker Verification (ASV) system is a type of bio-metric
authentication. It can be attacked by an intruder, who falsifies data in order
to get access to protected information. Countermeasures (CM) are special
algorithms that detect these spoofing-attacks. While the ASVspoof Challenge
series were focused on the development of CM for fixed ASV system, the new
Spoofing Aware Speaker Verification (SASV) Challenge organizers believe that
best results can be achieved if CM and ASV systems are optimized jointly. One
of the approaches for cooperative optimization is a fusion over embeddings or
scores obtained from ASV and CM models. The baselines of SASV Challenge 2022
present two types of fusion: score-sum and back-end ensemble with a 3-layer
MLP. This paper describes our research of other fusion methods, including
boosting over embeddings, which has not been used in anti-spoofing studies
before.
