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End of preview.
Bark detection dataset
Dataset Description
This dataset comprises both positive and negative samples of audio of 1 second in WAV format, recorded at 44.1kHz.
Negative samples include music, voice, claps, whistles and vacuum cleaner noise, among other sound you may record inside a house.
Caveats:
- This is an imbalanced dataset: ~10k negatives vs ~500 positives.
- Positive samples may include human generated barks.
- Some (few) positive samples are false positives.
Example usage
from datasets import load_dataset
dataset = load_dataset("rmarcosg/bark-detection", split="train")
Supported Tasks
- audio-classification: This dataset was created for the task of binary classification.
Dataset Structure
{
'file_id': '20221203_185908.wav',
'audio': {
'path': 'train/no/20221203_185908.wav',
'array': array([ 6.10351562e-05, -3.05175781e-05, -3.05175781e-05, ...,
6.10351562e-05, -1.22070312e-04, 1.83105469e-04]),
'sampling_rate': 44100
},
'label': 'no'
}
Additional Information
Licensing Information
The dataset is available under the Apache 2.0 license.
Citation Information
Please cite the dataset when using it as:
@InProceedings{huggingface:dataset,
title = {A bark detection dataset with positive and negative samples of 1 second},
author={Rodrigo Marcos García},
year={2024}
}
Contributions
Thanks to Greta (my dog) for its help.
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