  This paper proposes a benchmark of submissions to Detection and
Classification Acoustic Scene and Events 2021 Challenge (DCASE) Task 4
representing a sampling of the state-of-the-art in Sound Event Detection task.
The submissions are evaluated according to the two polyphonic sound detection
score scenarios proposed for the DCASE 2021 Challenge Task 4, which allow to
make an analysis on whether submissions are designed to perform fine-grained
temporal segmentation, coarse-grained temporal segmentation, or have been
designed to be polyvalent on the scenarios proposed. We study the solutions
proposed by participants to analyze their robustness to varying level target to
non-target signal-to-noise ratio and to temporal localization of target sound
events. A last experiment is proposed in order to study the impact of
non-target events on systems outputs. Results show that systems adapted to
provide coarse segmentation outputs are more robust to different target to
non-target signal-to-noise ratio and, with the help of specific data
augmentation methods, they are more robust to time localization of the original
event. Results of the last experiment display that systems tend to spuriously
predict short events when non-target events are present. This is particularly
true for systems that are tailored to have a fine segmentation.
