  The SdSv challenge Task 2 provided an opportunity to assess efficiency and
robustness of modern text-independent speaker verification systems. But it also
made it possible to test new approaches, capable of taking into account the
main issues of this challenge (duration, language, ...). This paper describes
the contributions of our laboratory to the speaker recognition field. These
contributions highlight two other challenges in addition to short-duration and
language: the mismatch between enrollment and test data and the one between
subsets of the evaluation trial dataset. The proposed approaches experimentally
show their relevance and efficiency on the SdSv evaluation, and could be of
interest in many real-life applications.
