Automatic detection and classification of beluga whale calls in the St. Lawrence estuary.

IF 2.1 2区 物理与天体物理 Q2 ACOUSTICS
Tristan Cotillard, Xavier Sécheresse, Jaclyn Aubin, Marie-Ana Mikus, Valeria Vergara, Sébastien Gambs, Robert Michaud, Cristiane C A Martins, Samuel Turgeon, Clément Chion, Irene Roca
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引用次数: 0

Abstract

The endangered beluga whale (Delphinapterus leucas) of the St. Lawrence Estuary (SLEB) faces threats from a variety of anthropogenic factors. Since belugas are a highly social and vocal species, passive acoustic monitoring has the potential to deliver, in a non-invasive and continuous way, real-time information on SLEB spatiotemporal habitat use, which is crucial for their monitoring and conservation. In this study, we introduce an automatic pipeline to analyze continuous passive acoustic data and provide standard and accurate estimations of SLEB acoustic presence and vocal activity. An object detector extracted vocalizations of beluga whales from an acoustic recording of beluga vocal activity. Then, two deep learning classifiers discriminated between high-frequency call types (40-120 kHz) and the presence of low-frequency components (0-20 kHz), respectively. Different algorithms were tested for each step and their main combinations were compared in time and performance. We focused our work on a high residency area, Baie Sainte-Marguerite (BSM), used for socialization and feeding by SLEB. Overall, this project showed that accurate continuous analysis of SLEB vocal activity at BSM could provide valuable information to estimate habitat use, link beluga behavior and acoustic activity within and between herds, and quantify beluga presence and abundance.

圣劳伦斯河口白鲸叫声的自动探测与分类。
圣劳伦斯河口(SLEB)濒临灭绝的白鲸(Delphinapterus leucas)面临着各种人为因素的威胁。由于白鲸是一种高度群居和发声的物种,被动声学监测有可能以非侵入性和连续的方式提供关于SLEB时空栖息地使用的实时信息,这对它们的监测和保护至关重要。在这项研究中,我们引入了一个自动管道来分析连续的被动声学数据,并提供标准和准确的SLEB声学存在和声乐活动估计。一个物体探测器从白鲸发声活动的录音中提取了白鲸的发声。然后,两个深度学习分类器分别区分高频呼叫类型(40-120 kHz)和低频成分(0-20 kHz)的存在。对不同算法进行了测试,并对其主要组合进行了时间和性能比较。我们的工作重点是一个高居住区域,Baie Sainte-Marguerite (BSM),用于SLEB的社交和喂养。总体而言,本项目表明,准确的连续分析白鲸在BSM的发声活动可以提供有价值的信息,以估计栖息地的利用,将白鲸的行为与群内和群间的声音活动联系起来,并量化白鲸的存在和丰度。
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来源期刊
CiteScore
4.60
自引率
16.70%
发文量
1433
审稿时长
4.7 months
期刊介绍: Since 1929 The Journal of the Acoustical Society of America has been the leading source of theoretical and experimental research results in the broad interdisciplinary study of sound. Subject coverage includes: linear and nonlinear acoustics; aeroacoustics, underwater sound and acoustical oceanography; ultrasonics and quantum acoustics; architectural and structural acoustics and vibration; speech, music and noise; psychology and physiology of hearing; engineering acoustics, transduction; bioacoustics, animal bioacoustics.
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