Analysing animal vocalisations in detail provides insights into the biomechanics, decision making and sensory processes behind their behaviours. Echolocating bats, and in particular, the CF-FM calls of high-duty cycle bats serve as a convenient model system to illustrate this point. The CF component in the CF-FM call is used for prey detection and the FM component is used in target ranging. According to the behavioural context at hand such as flight with conspecifics or prey capture, bats choose to increase the duration, intensity or spectral range of the components differently. Studying the call component alterations requires an objective methodology that first segments the components and then allows measurements on them. Studies till now have segmented the call components manually, or automatically using what I term the 'peak-frequency' method. Manual segmentation is error prone, while the 'peak-frequency' method requires on-axis recordings for good results. Despite multiple papers using a peak-frequency based segmentation, there remain no publicly available software implementations. itsfm is an open-source package that fills this gap with two implemntations that can segment CF-FM calls, one of them being an implementation of the peak-percentage method. itsfm additionally introduces the 'pseudo-Wigner-Ville distribution' (PWVD) method for call segmentation, thus allowing the segmentation of calls captured under a wider variety of recording conditions. I create a synthetic dataset and assess the performance of the PWVD method and the 'peak-frequency' method. The PWVD performs consistently well in call component segmentation in comparison to the peak-percentage method. I also discuss the supporting methods in the itsfm package that can help the further automatic segmentation, measurement and analysis of sounds. Though originally developed for the segmentation and measurement of CF-FM bat calls, the methods in itsfm are species-agnostic, and may be used for vocalisations of any type.

中文翻译：

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itsfm，一种开源软件包，可通过调频可靠地分割和测量声音

详细分析动物的发声可以洞察其行为背后的生物力学，决策和感觉过程。回声蝙蝠，特别是高占空比蝙蝠的CF-FM调用，是说明这一点的便捷模型系统。CF-FM呼叫中的CF分量用于猎物检测，而FM分量用于目标测距。根据当前的行为情况，例如带有特定物种的飞行或捕获猎物，蝙蝠选择不同地增加组件的持续时间，强度或光谱范围。研究呼叫组件变更需要一种客观的方法，该方法首先对组件进行细分，然后对它们进行测量。到目前为止，研究一直以手动方式或使用我所说的“峰值频率”自动划分了通话成分 方法。手动分割容易出错，而“峰值频率”方法需要在轴上进行记录才能获得良好的效果。尽管有多篇论文使用基于峰值频率的分割方法，但仍然没有公开可用的软件实现。itsfm是一个开源软件包，它通过两个可以细分CF-FM调用的内涵来填补这一空白，其中之一是Peak-percentage方法的实现。itsfm还引入了“伪Wigner-Ville分配”（PWVD）方法来进行呼叫分段，从而可以对在多种记录条件下捕获的呼叫进行分段。我创建了一个综合数据集，并评估了PWVD方法和“峰值频率”方法的性能。与峰值百分比方法相比，PWVD在呼叫成分分割中始终表现出色。我还将讨论itsfm中的支持方法软件包，可以帮助进一步自动分割，测量和分析声音。虽然最初是为的CF-FM蝙蝠呼叫的分割和测量的发展，在方法itsfm是种无关，并且可用于任何类型的发声。