Department of Physics, University of New Orleans, New Orleans, Louisiana 70148, USA.
J Acoust Soc Am. 2018 Jul;144(1):387. doi: 10.1121/1.5047435.
This study presents and evaluates several methods for automated species-level classification of echolocation clicks from three beaked whale species recorded in the northern Gulf of Mexico. The species included are Cuvier's and Gervais' beaked whales, as well as an unknown species denoted Beaked Whale Gulf. An optimal feature set for discriminating the three click types while also separating detected clicks from unidentified delphinids was determined using supervised step-wise discriminant analysis. Linear and quadratic discriminant analyses both achieved error rates below 1% with three features, determined by tenfold cross validation. The waveform fractal dimension was found to be a highly ranked feature among standard spectral and temporal parameters. The top-ranking features were Higuchi's fractal dimension, spectral centroid, Katz's fractal dimension, and -10 dB duration. Six clustering routines, including four popular network-based algorithms, were also evaluated as unsupervised classification methods using the selected feature set. False positive rates of 0.001 and 0.024 were achieved by Chinese Whispers and spectral clustering, respectively, across 200 randomized trials. However, Chinese Whispers clustering yielded larger false negative rates. Spectral clustering was further tested on clicks from encounters of beaked, sperm, and pilot whales in the Tongue of the Ocean, Bahamas.
本研究提出并评估了几种自动物种分类方法，用于对墨西哥湾北部记录的三种喙鲸物种的回声定位咔哒声进行分类。包括 Cuvier 喙鲸和 Gervais 喙鲸，以及一种未知物种被称为喙鲸墨西哥湾。通过监督逐步判别分析，确定了一个最佳的特征集，用于区分三种咔哒声类型，同时还将检测到的咔哒声与未识别的海豚类动物区分开来。线性和二次判别分析都在使用 10 倍交叉验证确定的三个特征下达到了低于 1%的错误率。发现波形分形维数是标准光谱和时间参数中排名较高的特征之一。排名最高的特征是 Higuchi 的分形维数、光谱质心、Katz 的分形维数和-10dB 持续时间。六种聚类程序，包括四种流行的基于网络的算法，也使用选定的特征集作为无监督分类方法进行了评估。在 200 次随机试验中，通过 Chinese Whispers 和光谱聚类分别实现了 0.001 和 0.024 的假阳性率。然而，Chinese Whispers 聚类的假阴性率更高。进一步在巴哈马 Tongue of the Ocean 中记录的喙鲸、抹香鲸和领航鲸的咔哒声上测试了光谱聚类。
