Electrical Measurements, Lund University, Box 118, SE-221 00 Lund, Sweden.
J Acoust Soc Am. 2011 Jan;129(1):458-66. doi: 10.1121/1.3519404.
Recordings of the acoustic activity of free-swimming groups of echolocating dolphins increase the likelihood of collecting overlapping click trains, originating from multiple individuals, in the same set of data. In order to evaluate the click properties of each individual based on such recordings it is necessary to identify which clicks originate from which animal. This paper suggests a computationally efficient strategy to separate overlapping click trains originating from multiple free-swimming bottlenose dolphins, enabling echolocation analysis at an individual level on several animals. This technique is based on sequential matching of the frequency spectra of successive clicks. The clicks are grouped together as individual click trains if the correlation coefficients between clicks are higher than a pre-set threshold level. The robustness of the algorithm is tested by adding artificially generated white Gaussian noise and comparing the results with other comparable commonly used methods based on inter-click intervals, centroid frequencies, and amplitude levels. The described method is applicable to a variety of experimental and observational contexts, e.g., those regarding echolocation development of calves, the hypothesized acoustic "etiquette" among dolphins when investigating the same object, and the possible occurrence of eavesdropping in large dolphin pods.
对自由游动的回声定位海豚群体的声学活动进行记录,增加了在同一组数据中收集来自多个个体的重叠 click 序列的可能性。为了根据这些记录评估每个个体的 click 属性,有必要识别哪些 click 源自哪个动物。本文提出了一种计算效率高的策略,可以将源自多个自由游动的宽吻海豚的重叠 click 序列分离,从而能够在多个动物上进行个体水平的回声定位分析。该技术基于连续点击频谱的顺序匹配。如果两个 click 之间的相关系数高于预设的阈值水平,则将它们分组为单个 click 序列。该算法的稳健性通过添加人为生成的高斯白噪声进行测试,并将结果与基于 click 间隔、质心频率和幅度水平的其他可比常用方法进行比较。所描述的方法适用于各种实验和观测情境,例如,幼海豚回声定位发展、海豚在研究同一物体时假设的声学“礼仪”,以及在大型海豚群体中可能发生的偷听。