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Environmental sound scene and sound event recognition is important for therecognition of suspicious events in indoor and outdoor environments (such asnurseries, smart homes, nursing homes, etc.) and is a fundamental task involvedin many audio surveillance applications. In particular, there is no publiccommon data set for the research field of sound event recognition for the dataset of the indoor environmental sound scene. Therefore, this paper proposes adata set (called as AGS) for the home environment sound. This data setconsiders various types of overlapping audio in the scene, background noise.Moreover, based on the proposed data set, this paper compares and analyzes theadvanced methods for sound event recognition, and then illustrates thereliability of the data set proposed in this paper, and studies the challengesraised by the new data set. Our proposed AGS and the source code of thecorresponding baselines at https://github.com/taolunzu11/AGS .

AGS: An Dataset and Taxonomy for Domestic Scene Sound Event Recognition