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Official code repo for the paper "Automatic Sound Event Detection and Classification of Great Ape Calls Using Neural Networks"

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Automatic Sound Event Detection and Classification of Great Ape Calls Using Neural Networks

Citation

Please cite our preprint (Arxiv) and our paper (ICPhS) as follows:

@inproceedings{jiang-etal-2023-automatic,
    title = "Automatic Sound Event Detection and Classification of Great Ape Calls Using Neural Networks",
    author = {Jiang, Zifan and Soldati, Adrian and Schamberg, Isaac and Lameira, Adriano R and Moran, Steven},
    booktitle = "Proceedings of the 20th International Congress of Phonetic Sciences (ICPhS 2023)",
    pages = "3121--3125",
    month = august,
    year = "2023",
    address = "Prague, the Czech Republic"
}

Data

Prepare each data set in a data_xxx directory, which contains:

  • a raw/ directory of raw data, including recordings and annotations
  • some scripts to preprocess the raw data
  • preprocessed data in possibly different splits

Model

To train a model, make a model directory with a config.json inside of models directory.

Train

For example:

python model.py -c models/chimp_wav2vec2_lstm_0/config.json

TensorBoard

tensorboard --logdir=runs

Results

See https://github.com/J22Melody/sed_great_ape/blob/main/model_stats.csv.

Visualize

See https://github.com/J22Melody/sed_great_ape/tree/main/visualization.

Legacy

See previous exploration logs in https://github.com/J22Melody/sed_great_ape/tree/main/legacy.

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Official code repo for the paper "Automatic Sound Event Detection and Classification of Great Ape Calls Using Neural Networks"

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