  The aim of the Detection and Classification of Acoustic Scenes and Events
Challenge Task 4 is to evaluate systems for the detection of sound events in
domestic environments using an heterogeneous dataset. The systems need to be
able to correctly detect the sound events present in a recorded audio clip, as
well as localize the events in time. This year's task is a follow-up of DCASE
2021 Task 4, with some important novelties. The goal of this paper is to
describe and motivate these new additions, and report an analysis of their
impact on the baseline system. We introduced three main novelties: the use of
external datasets, including recently released strongly annotated clips from
Audioset, the possibility of leveraging pre-trained models, and a new energy
consumption metric to raise awareness about the ecological impact of training
sound events detectors. The results on the baseline system show that leveraging
open-source pretrained on AudioSet improves the results significantly in terms
of event classification but not in terms of event segmentation.
