Data-efficient self-supervised algorithms for fine-grained birdsong analysis
Research in bioacoustics, neuroscience, and linguistics often uses birdsong as a proxy to acquire knowledge across diverse areas. This requires audio models to annotate and parse the birdsong. Developing such models requires precise, syllable-level annotated training data. Therefore, automated metho...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Elsevier
2026-06-01
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| Series: | Ecological Informatics |
| Assuntos: | |
| Acceso en liña: | http://www.sciencedirect.com/science/article/pii/S1574954126002682 |
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