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环境噪声数据集用于声音事件分类和检测
Luca Fredianelli1, Francesco Artuso2, Geremia Pompei3
1Institute for Chemical-Physical Processes of the Italian Research Council, Via Moruzzi 1, 56100, Pisa, Italy. luca.fredianelli@cnr.it.
Scientific data
|October 30, 2025
概括
本研究介绍了DataSEC和DataSED,两种用于声音事件分类和检测的开放访问数据集. 这些数据集有助于研究分析环境噪音和在现实环境中识别声音源.
科学领域:
- 声学和信号处理
- 机器学习应用 机器学习应用
- 环境科学 环境科学
背景情况:
- 音频事件分类 (SEC) 和检测 (SED) 对于分析音频数据越来越重要.
- 在杂的户外环境中识别声音源是一个重大挑战.
- 现有的数据集往往在范围和真实性方面存在局限性.
研究的目的:
- 为了引入两个新的,开放式访问数据集,DataSEC和DataSED.
- 解决现有的声音事件数据集中发现的漏洞.
- 支持对现实世界声音事件分类和环境噪声自动化分析的研究.
主要方法:
- 收集了超过35个小时的真实,非合成的 .wav 音频数据.
- 利用声级计测量和在线存储库来获取数据.
- 结构化数据SEC具有4292个单一事件样本,跨22个类和28个子类.
- 开发了具有712条记录和超过4000个标签的数据SED.csv格式.
主要成果:
- 数据SEC提供分类单个声音事件.
- 数据SED提供了具有详细事件标签的多事件记录.
- 数据集涵盖了各种各样的城市和农村环境.
- 这些数据集包含真实的,现实世界的音频录音.
结论:
- 数据SEC和DataSED为SEC和SED的研究提供了宝贵的资源.
- 这些数据集有助于开发可靠的环境声音分析算法.
- 开放式访问的性质促进了该领域的进一步研究和开发.
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