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Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan

机译:通过音频分离感应生态系统动态:台湾东北部海洋音乐探究

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Remote acquisition of information on ecosystem dynamics is essential for conservation management, especially for the deep ocean. Soundscape offers unique opportunities to study the behavior of soniferous marine animals and their interactions with various noisegenerating activities at a fine temporal resolution. However, the retrieval of soundscape information remains challenging owing to limitations in audio analysis techniques that are effective in the face of highly variable interfering sources. This study investigated the application of a seafloor acoustic observatory as a long-term platform for observing marine ecosystem dynamics through audio source separation. A source separation model based on the assumption of source-specific periodicity was used to factorize time-frequency representations of long-duration underwater recordings. With minimal supervision, the model learned to discriminate source-specific spectral features and prove to be effective in the separation of sounds made by cetaceans, soniferous fish, and abiotic sources from the deepwater soundscapes off northeastern Taiwan. Results revealed phenological differences among the sound sources and identified diurnal and seasonal interactions between cetaceans and soniferous fish. The application of clustering to source separation results generated a database featuring the diversity of soundscapes and revealed a compositional shift in clusters of cetacean vocalizations and fish choruses during diurnal and seasonal cycles. The source separation model enables the transformation of single-channel audio into multiple channels encoding the dynamics of biophony, geophony, and anthropophony, which are essential for characterizing the community of soniferous animals, quality of acoustic habitat, and their interactions. Our results demonstrated the application of source separation could facilitate acoustic diversity assessment, which is a crucial task in soundscape-based ecosystem monitoring. Future implementation of soundscape information retrieval in long-term marine observation networks will lead to the use of soundscapes as a new tool for conservation management in an increasingly noisy ocean.
机译:远程获取关于生态系统动态的信息对于保护管理至关重要,特别是对于深海。 Soundscape提供了独特的机会,以便在良好的时间分辨率下研究顽强的海洋动物的行为及其与各种噪声创新活动的相互作用。然而,由于在高度可变干扰源的面部有效的音频分析技术的局限性,声景信息的检索仍然具有挑战性。本研究调查了海底声学天文台作为长期平台,通过音频分离观察海洋生态系统动态。基于源特定周期性的假设的源分离模型用于分解长期水下记录的时频表示。通过极少的监督,该模型学会了鉴别源特定的谱特征,并证明是在台湾东北部靠近深水出版物的鲸类,麻烦的鱼类和非生物来源的声音分离。结果揭示了声源和依锡和经肉类之间的昼夜季节性相互作用的鉴别差异。聚类应用于源分离结果的应用产生了具有声音变化的多样性的数据库,并在昼夜和季节性循环期间揭示了鲸类声学和鱼合唱团簇的组成转变。源分离模型使单通道音频的转换为编码私人,地球部和人类动态的多个通道,这对于特征是表征顽强动物的社区,声学栖息地的群体以及它们的相互作用至关重要。我们的结果表明,源分离的应用可以促进声学分流评估,这是基于Soundcape的生态系统监测中的一个重要任务。在长期海洋观测网络中检索声景信息的未来实施将导致SoundScapes作为越来越嘈杂的海洋中保护管理的新工具。

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