Abstract
Bioacoustics is powerful for monitoring biodiversity. We investigate in this paper automatic segmentation model for real-world bioacoustic scenes in order to infer hidden states referred as song units. Nevertheless, the number of these acoustic units is often...
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CITATION STYLE
APA
Roger, V., Bartcus, M., Chamroukhi, F., & Glotin, H. (2018). Unsupervised Bioacoustic Segmentation by Hierarchical Dirichlet Process Hidden Markov Model. In Multimedia Tools and Applications for Environmental & Biodiversity Informatics (pp. 113–130). Springer International Publishing. https://doi.org/10.1007/978-3-319-76445-0_7
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