  In this article, we describe Conditioned Localizer and Classifier (CoLoC)
which is a novel solution for Sound Event Localization and Detection (SELD).
The solution constitutes of two stages: the localization is done first and is
followed by classification conditioned by the output of the localizer. In order
to resolve the problem of the unknown number of sources we incorporate the idea
borrowed from Sequential Set Generation (SSG). Models from both stages are
SELDnet-like CRNNs, but with single outputs. Conducted reasoning shows that
such two single-output models are fit for SELD task. We show that our solution
improves on the baseline system in most metrics on the STARSS22 Dataset.
