Model that tags audio files as belonging to one or more of 29 (t.b.d. below) prevalent Orthoptera species within the Biodiversity Exploratories.

To use the model, you have to install autrainer, e.g. via pip:

This model has been trained and tested with autrainer version 0.6.0. For more information about autrainer, please refer to: https://autrainer.github.io/autrainer/index.html

The model can be applied on all wav files present in a folder (<data-root>) and stored in another folder (<output-root>):

, where -w is the window size in seconds, -s is the step size in seconds and -sr is the sampling rate. For other possible inference settings and all usable parameters, please have a look at the autrainer documentation. However, the above settings are recommended.

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The audio recordings were resampled to 96kHz, as we wanted to avoid losing too much frequency information from the species. Log-Mel spectrograms were then extracted using torchlibrosa.

The model has been trained for 30 epochs. At the end of each epoch, the model was evaluated on our validation set. We release the state that achieved the best performance on this validation set. All training hyperparameters can be found inside conf/config.yaml inside the model folder.

The performance on the test set reached a (macro) f1-score of 0.70.

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Please acknowledge the work which produced the original model. We would appreciate an acknowledgment to autrainer.