Acoustic recordings of three Hainan gibbon (Nomascus hainanus) social groups for machine learning and deep learning analyses

Kabuga, EORCID logo; Durfourq, EORCID logo; Luphade, NL; Turvey, T., ST; Ma, H; Cheyne, SM; Lui, H; Bryant, JV; Chen, Q; Li, W; Liu, Z; Zhou, Z; Britz, S; Bah, BORCID logo and Durbach, IORCID logo (2026). Acoustic recordings of three Hainan gibbon (Nomascus hainanus) social groups for machine learning and deep learning analyses. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.20698864
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This dataset is released as a companion resource to the paper “Passive acoustic identification of social groups in the Hainan gibbon” (DOI: https://doi.org/10.1002/rse2.70088). It contains the acoustic recordings used in the study and is provided to enable reproducible benchmarking and methodological development in bioacoustic machine learning. The recordings were collected from three distinct Hainan gibbon (Nomascus hainanus) social groups in natural habitat conditions and are intended for use in machine learning and deep learning applications, including social group identification, bioacoustic classification, and ecological monitoring. The dataset includes raw audio files, corresponding phrase-level annotations, and segment-level annotations. In addition, it provides predefined training, validation, and test partitions used in the original study to support reproducible training and evaluation of segment- and sequence-based models.

Keywords

Hainan gibbon; Nomascus hainanus; bioacoustics; Acoustic recording; Animal vocalizations; Wild audio dataset; Group identification; Ecological monitoring; Machine learning; Deep learning

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