1. Audio recording devices have changed significantly over the last 50 years, making large datasets of recordings of natural sounds, such as birdsong, easier to obtain. This increase in digital recordings necessitates an increase in high‐throughput methods of analysis for researchers. Specifically, there is a need in the community for open‐source methods that are tailored to recordings of varying qualities and from multiple species collected in nature.
2. We developed Chipper, a Python‐based software to semi‐automate both the segmentation of acoustic signals and the subsequent analysis of their frequencies and durations. For avian recordings, we provide widgets to best determine appropriate thresholds for noise and syllable similarity, which aid in calculating note measurements and determining song syntax. In addition, we generated a set of synthetic songs with various levels of background noise to test Chipper's accuracy, repeatability and reproducibility.
3. Chipper provides an effective way to quickly generate quantitative, reproducible measures of birdsong. The cross‐platform graphical user interface allows the user to adjust parameters and visualize the resulting spectrogram and signal segmentation, providing a simplified method for analysing field recordings.
4. Chipper streamlines the processing of audio recordings with multiple user‐friendly tools and is optimized for multiple species and varying recording qualities. Ultimately, Chipper supports the use of citizen‐science data and increases the feasibility of large‐scale multi‐species birdsong studies.

中文翻译：

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Chipper：用于半自动分割和分析鸟鸣和其他自然声音的开源软件

1. 在过去的50年中，音频记录设备发生了显着变化，这使得获取诸如鸟鸣之类的自然声音记录的大型数据集变得更加容易。数字记录的增加有必要增加研究人员的高通量分析方法。特别是，社区中需要一种开源方法，这些方法适合于记录不同质量的记录，并来自自然界中采集的多种物种。
2. 我们开发了Chipper，这是一种基于Python的软件，可将声信号的分割以及随后对其频率和持续时间的分析半自动化。对于鸟类录音，我们提供的小部件可以最佳地确定噪音和音节相似度的适当阈值，从而有助于计算音符大小和确定歌曲语法。此外，我们还制作了一组带有各种背景噪音的合成歌曲，以测试Chipper的准确性，可重复性和可再现性。
3. 削片机提供了一种有效的方法，可以快速生成定量的，可重复的鸟鸣测量。跨平台的图形用户界面允许用户调整参数并可视化最终的频谱图和信号分段，从而提供了一种简化的现场记录分析方法。
4. Chipper使用多种用户友好工具简化了音频记录的处理，并且针对多种种类和不同的记录质量进行了优化。最终，Chipper支持公民科学数据的使用，并增加了大规模多物种鸟类研究的可行性。