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

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 noise-generating activities at a fine tempora...

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Detalles Bibliográficos
Autores principales: Lin, Tzu-Hao, Akamatsu, Tomonari, Tsao, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891715/
https://www.ncbi.nlm.nih.gov/pubmed/33600436
http://dx.doi.org/10.1371/journal.pcbi.1008698
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author Lin, Tzu-Hao
Akamatsu, Tomonari
Tsao, Yu
author_facet Lin, Tzu-Hao
Akamatsu, Tomonari
Tsao, Yu
author_sort Lin, Tzu-Hao
collection PubMed
description 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 noise-generating 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 deep-water 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.
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spelling pubmed-78917152021-02-25 Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan Lin, Tzu-Hao Akamatsu, Tomonari Tsao, Yu PLoS Comput Biol Research Article 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 noise-generating 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 deep-water 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. Public Library of Science 2021-02-18 /pmc/articles/PMC7891715/ /pubmed/33600436 http://dx.doi.org/10.1371/journal.pcbi.1008698 Text en © 2021 Lin et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lin, Tzu-Hao
Akamatsu, Tomonari
Tsao, Yu
Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan
title Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan
title_full Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan
title_fullStr Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan
title_full_unstemmed Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan
title_short Sensing ecosystem dynamics via audio source separation: A case study of marine soundscapes off northeastern Taiwan
title_sort sensing ecosystem dynamics via audio source separation: a case study of marine soundscapes off northeastern taiwan
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891715/
https://www.ncbi.nlm.nih.gov/pubmed/33600436
http://dx.doi.org/10.1371/journal.pcbi.1008698
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