DCASE2019_task4_synthetic_data

Synthetic data for DCASE 2019 task 4 Freesound dataset [1,2]: A subset of FSD is used as foreground sound events for the synthetic subset of the dataset for DCASE 2019 task 4. FSD is a large-scale, general-purpose audio dataset composed of Freesound content annotated with labels from the AudioSet Ontology [3]. SINS dataset [4]: The derivative of the SINS dataset used for DCASE2018 task 5 is used as background for the synthetic subset of the dataset for DCASE 2019 task 4. The SINS dataset contains a continuous recording of one person living in a vacation home over a period of one week. It was collected using a network of 13 microphone arrays distributed over the entire home. The microphone array consists of 4 linearly arranged microphones. The synthetic set is composed of 10 sec audio clips generated with Scaper [5]. The foreground events are obtained from FSD. Each event audio clip was verified manually to ensure that the sound quality and the event-to-background ratio were sufficient to be used an isolated event. We also verified that the event was actually dominant in the clip and we controlled if the event onset and offset are present in the clip. Each selected clip was then segmented when needed to remove silences before and after the event and between events when the file contained multiple occurrences of the event class. License: All sounds comming from FSD are released under Creative Commons licences. Synthetic sounds can only be used for competition purposes until the full CC license list is made available at the end of the competition. Further information on dcase website. References: [1] F. Font, G. Roma & X. Serra. Freesound technical demo. In Proceedings of the 21st ACM international conference on Multimedia. ACM, 2013. [2] E. Fonseca, J. Pons, X. Favory, F. Font, D. Bogdanov, A. Ferraro, S. Oramas, A. Porter & X. Serra. Freesound Datasets: A Platform for the Creation of Open Audio Datasets. In Proceedings of the 18th International Society for Music Information Retrieval Conference, Suzhou, China, 2017. [3] Jort F. Gemmeke and Daniel P. W. Ellis and Dylan Freedman and Aren Jansen and Wade Lawrence and R. Channing Moore and Manoj Plakal and Marvin Ritter. Audio Set: An ontology and human-labeled dataset for audio events. In Proceedings IEEE ICASSP 2017, New Orleans, LA, 2017. [4] Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, and Peter Karsmakers. The SINS database for detection of daily activities in a home environment using an acoustic sensor network. In Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), 32–36. November 2017. [5] J. Salamon, D. MacConnell, M. Cartwright, P. Li, and J. P. Bello. Scaper: A library for soundscape synthesis and augmentation In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), New Paltz, NY, USA, Oct. 2017.

用于DCASE（Detection and Classification of Acoustic Scenes and Events，声学场景与事件检测与分类）2019任务4的Freesound数据集（Freesound Dataset，简称FSD）合成数据：本数据集的合成子集以FSD的一个子集作为前景声事件素材。FSD是一个大规模通用音频数据集，其内容源自Freesound平台，并采用AudioSet本体（AudioSet Ontology）[3]中的标签进行标注。
SINS数据集[4]：本数据集的合成子集采用DCASE 2018任务5所使用的SINS数据集衍生版本作为背景音素材。SINS数据集包含一名受试者在度假小屋内为期一周的连续录音，采集方案为在全屋部署13个麦克风阵列组成的采集网络，每个麦克风阵列由4个线性排列的麦克风构成。
本合成数据集的音频片段均采用Scaper[5]生成，单段音频时长为10秒。前景声事件均源自FSD数据集。我们对每一段事件音频片段进行了人工校验，确保其音质以及事件背景比满足作为独立声事件的使用要求。同时我们也会验证该事件确实为片段中的主导声，并确认片段中包含事件的起始与结束时刻。对于筛选出的片段，我们会根据需要进行分段处理，去除事件前后以及同一事件类多次出现时相邻事件之间的静音片段。
授权条款：所有源自FSD的音频素材均采用知识共享（Creative Commons，简称CC）协议发布。在竞赛结束并公布完整的CC许可列表之前，合成音频仅可用于本次竞赛相关用途。
更多详细信息可查阅DCASE官方网站。
参考文献：
[1] F. Font, G. Roma & X. Serra. Freesound技术演示. 见：第21届ACM国际多媒体大会会议论文集. ACM, 2013.
[2] E. Fonseca, J. Pons, X. Favory, F. Font, D. Bogdanov, A. Ferraro, S. Oramas, A. Porter & X. Serra. Freesound数据集：开放音频数据集创建平台. 见：第18届国际音乐信息检索学会会议论文集，中国苏州，2017.
[3] Jort F. Gemmeke, Daniel P. W. Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R. Channing Moore, Manoj Plakal & Marvin Ritter. Audio Set：面向音频事件的本体与人工标注数据集. 见：2017年IEEE国际声学、语音与信号处理大会（ICASSP）论文集，美国路易斯安那州新奥尔良，2017.
[4] Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst & Peter Karsmakers. SINS数据库：基于声学传感器网络的家庭日常活动检测数据库. 见：2017年DCASE（声学场景与事件检测与分类）研讨会论文集，2017年11月，第32-36页.
[5] J. Salamon, D. MacConnell, M. Cartwright, P. Li & J. P. Bello. Scaper：声景合成与增强工具库. 见：IEEE声学信号处理应用与音频声学研讨会（WASPAA）论文集，美国纽约州新帕尔茨，2017年10月.

搜集汇总

背景与挑战

背景概述

DCASE2019_task4_synthetic_data是一个用于DCASE 2019任务4的合成音频数据集，专门针对声音事件检测任务。数据集由10秒音频剪辑组成，使用Scaper库生成，前景声音来自Freesound数据集，背景声音来自SINS数据集，并经过手动验证以确保音质和事件可检测性。该数据集主要用于竞赛目的，在竞赛期间合成声音的使用受到限制。