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Many animal species are known to show individuality in their acoustic communication. This variation in individual male signatures can be decisive for female choice. Within the damselfishes, Dascyllus species are known for prolific sound production during the realization of movements associated with courtship (i.

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Rapid urban development impacts the integrity of tropical ecosystems on broad spatiotemporal scales. However, sustained long-term monitoring poses significant challenges, particularly in tropical regions. In this context, ecoacoustics emerges as a promising approach to address this gap.

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This 11-year case study describes the acoustic behaviour of a resident Indian Ocean humpback dolphin during commercial swim-with-dolphin activities in Mozambique. Combining data collected using low-cost action cameras with full bandwidth hydrophone recordings, we identified a temporally stable stereotyped whistle contour that met the SIGnature IDentification bout criteria. This whistle was produced with potential information-enhancing features (bi-phonation and subtle variations in frequency modulation).

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The fundamental frequency (fo) is pivotal for quantifying vocal-fold characteristics. However, the accuracy of fo estimation in hoarse voices is notably low, and no definitive algorithm for fo estimation has been previously established. In this study, we introduce an algorithm named, "Spectral-based fo Estimator Emphasized by Domination and Sequence (SFEEDS)," which enhances the spectrum method and conducted comparative analyses with conventional estimation methods.

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Passive acoustic monitoring (PAM) is an increasingly popular tool to study vocalising species. The amount of data generated by PAM studies calls for robust automatic classifiers. Deep learning (DL) techniques have been proven effective in identifying acoustic signals in challenging datasets, but due to their black-box nature their underlying biases are hard to quantify.

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