Deep Learning for Ethoacoustics of Orcas on three years pentaphonic continuous recording at Orcalab revealing tide, moon and diel effects
Autor: | Poupard, Marion, Best, Paul, Schlüter, Jan, Prévot, Jean-Marc, Symonds, Helena, Spong, Paul, Glotin, Hervé |
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Přispěvatelé: | Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), DYNamiques de l’Information (DYNI), Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Représentations musicales (Repmus), Sciences et Technologies de la Musique et du Son (STMS), Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), PNRIA, Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU), Poupard, Marion |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
[SDE] Environmental Sciences
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI] Cetaceans Orcinus orca Convolutional Neural Networks Ethoacoustics [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] [SDE.BE] Environmental Sciences/Biodiversity and Ecology Big data Deep Learning Orcas Soundscape [SDE]Environmental Sciences Environmental factors [SDE.BE]Environmental Sciences/Biodiversity and Ecology Bioacoustics |
Zdroj: | OCEANS OCEANS, Jun 2019, Marseille, France |
Popis: | International audience; One of the best ways of studying animals that produce signals in underwater environments is to use passive acoustic monitoring (PAM). Acoustic monitoring is used to study marine mammals in oceans, and gives us information for understanding cetacean life, such as their behaviour, movement or reproduction. Automated analysis for captured sound is almost essential because of the large quantity of data. A deep learning approach was chosen for this task, since it has proven great efficiency for answering such problematics. This study focused on the orcas (Orcinus orca) of northern Vancouver Island, Canada, in collaboration with the NGO Orcalab which developed a multi-hydrophone recording station around Hanson Island to study orcas. The acoustic station is composed of 5 hydrophones and extends over 50 km 2 of ocean. Since 2016 we are continuously streaming the hydrophone signals to our laboratory at Toulon, France, yielding nearly 50 TB of synchronous multichannel recordings. The objective for this research is to do a preliminary analysis of the collected data and demonstrate influence of environmental factors (tidal, moon phase and daily period) on the orcas' acoustic activities. |
Databáze: | OpenAIRE |
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