Department of Organismal Biology and Anatomy, University of Chicago, 1027 East 57th Street, Chicago, Illinois 60622, USA.
J Acoust Soc Am. 2013 Aug;134(2):1407-15. doi: 10.1121/1.4812269.
Quantitative measures of acoustic similarity can reveal patterns of shared vocal behavior in social species. Many methods for computing similarity have been developed, but their performance has not been extensively characterized in noisy environments and with vocalizations characterized by complex frequency modulations. This paper describes methods of bioacoustic comparison based on dynamic time warping (DTW) of the fundamental frequency or spectrogram. Fundamental frequency is estimated using a Bayesian particle filter adaptation of harmonic template matching. The methods were tested on field recordings of flight calls from superb starlings, Lamprotornis superbus, for how well they could separate distinct categories of call elements (motifs). The fundamental-frequency-based method performed best, but the spectrogram-based method was less sensitive to noise. Both DTW methods provided better separation of categories than spectrographic cross correlation, likely due to substantial variability in the duration of superb starling flight call motifs.
声学相似性的定量测量可以揭示社交物种中共享发声行为的模式。已经开发出许多用于计算相似性的方法，但它们在嘈杂环境中和具有复杂频率调制的发声中的性能尚未得到广泛描述。本文描述了基于基频或声谱图的动态时间规整 (DTW) 的生物声学比较方法。基频使用基于贝叶斯粒子滤波器的谐波模板匹配进行估计。该方法在超级八哥的飞行叫声的现场录音上进行了测试，以评估它们在区分不同叫声元素 (主题) 类别方面的表现。基于基频的方法表现最佳，但基于声谱图的方法对噪声的敏感性较低。与声谱交叉相关相比，两种 DTW 方法都能更好地分离类别，这可能是由于超级八哥飞行叫声主题的持续时间存在很大的可变性。
