  Environmental sound scene and sound event recognition is important for the
recognition of suspicious events in indoor and outdoor environments (such as
nurseries, smart homes, nursing homes, etc.) and is a fundamental task involved
in many audio surveillance applications. In particular, there is no public
common data set for the research field of sound event recognition for the data
set of the indoor environmental sound scene. Therefore, this paper proposes a
data set (called as AGS) for the home environment sound. This data set
considers various types of overlapping audio in the scene, background noise.
Moreover, based on the proposed data set, this paper compares and analyzes the
advanced methods for sound event recognition, and then illustrates the
reliability of the data set proposed in this paper, and studies the challenges
raised by the new data set. Our proposed AGS and the source code of the
corresponding baselines at https://github.com/taolunzu11/AGS .
