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 .

翻译：环境声音场景与声音事件识别对于识别室内外环境（如托儿所、智能家居、养老院等）中的可疑事件具有重要意义，是众多音频监控应用中的基础性任务。当前，室内环境声音场景的声音事件识别研究领域尚缺乏公开的通用数据集。为此，本文提出一个面向家庭环境声音的数据集（称为AGS）。该数据集考虑了场景中多种类型的重叠音频及背景噪声。此外，基于所提出的数据集，本文比较和分析了当前声音事件识别的先进方法，验证了本数据集的可信度，并探讨了新数据集所带来的挑战。本文提出的AGS数据集及相应基线方法的源代码已发布于https://github.com/taolunzu11/AGS。