  As part of the 2016 public evaluation challenge on Detection and
Classification of Acoustic Scenes and Events (DCASE 2016), the second task
focused on evaluating sound event detection systems using synthetic mixtures of
office sounds. This task, which follows the `Event Detection - Office
Synthetic' task of DCASE 2013, studies the behaviour of tested algorithms when
facing controlled levels of audio complexity with respect to background noise
and polyphony/density, with the added benefit of a very accurate ground truth.
This paper presents the task formulation, evaluation metrics, submitted
systems, and provides a statistical analysis of the results achieved, with
respect to various aspects of the evaluation dataset.
