Published June 4, 2026 | Version v1.0.0

Acoustic individual identification in a species of field cricket using deep learning

  • 1. ROR icon University of Cape Town
  • 2. ROR icon African Institute for Mathematical Sciences
  • 3. ROR icon Azim Premji University
  • 4. ROR icon University of St Andrews
  • 5. Indian Institute of Science
  • 6. Medical Research Council Unit The Gambia

Description

This Zenodo archive preserves the source code and a representative subset of the data accompanying the paper:  "Acoustic individual identification in a species of field cricket using deep learning."

The repository contains all scripts required for data preprocessing, feature extraction, model development, training, evaluation, and reproduction of the computational workflow described in the publication.

To facilitate testing and reproducibility while maintaining a manageable Github archive size, only a representative subset of the dataset is included in this repository. This subset is sufficient to verify the installation, execute the analysis pipeline, and reproduce example experiments.

The complete dataset used in the study is archived separately and distributed through a dedicated Zenodo record:

Full Dataset: DOI: 10.5281/zenodo.20596912

Researchers wishing to reproduce the full experimental results reported in the publication should download the complete dataset from the dataset archive and follow the instructions provided in the repository documentation.

Reproducibility

This software release has been designed to support transparent and reproducible research. The included sample data enables users to validate the implementation and run the complete workflow, while the separate full dataset archive provides access to all recordings required to reproduce the results presented in the associated publication.

Files

kabuga1987/Cricket_Identification-v1.0.0.zip

Files (360.2 MB)

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