Oral presentation in 2018 ICEO & SI Conference
Studying wildlife activities by using soundscape information
Tzu-Hao Lin1, Yu Tsao2, Chun-Chia Huang3, and Mao-Ning Tuanmu3
1Department of Marine Biodiversity Research, Japan Agency for Marine-Earth Science and Technology
2Research Center for Information Technology Innovation, Academia Sinica
3Biodiversity Research Center, Academia Sinica
Information regarding biodiversity change is essential for the decision making of resource exploitation and conservation management. Studies on biodiversity are labor-intensive and time-consuming. Therefore, the development of a remote observation platform of wildlife is essential. In recent decades, passive acoustic monitoring has been widely employed to detect vocalizing animals. Besides, various environmental sounds and anthropogenic noises can also be recorded in a soundscape. Thus, a soundscape monitoring network has been considered as an acoustic sensing platform of the ecosystem. Although a significant amount of acoustic data can be collected, the acoustic data analysis remains a challenge for ecologists. In this study, we employed multiple layers of non-negative matrix factorization (NMF) to decompose a spectrogram into individual sound sources. Our results showed that echolocation calls produced from three different bat species can be effectively separated in an unsupervised manner. Even for overlapping signals, the deep NMF can still produce a reliable separation result. Therefore, the integration of NMF-based blind source separation and a soundscape monitoring network can reduce the difficulty of acoustic-based wildlife monitoring in the future.
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