Python library for downloading, loading & working with sound datasets. Find the API documentation here.
Inspired by and based on mirdata. (https://github.com/soundata/soundata)

This library provides tools for working with common sound datasets, including tools for:

• Downloading datasets to a common location and format
• Validating that the files for a dataset are all present
• Loading annotation files to a common format
• Parsing clip-level metadata for detailed evaluations

Here's soundata's list of currently supported datasets.

To install, simply run:

pip install soundata

import soundata

dataset = soundata.initialize('urbansound8k')
dataset.download()  # download the dataset
dataset.validate()  # validate that all the expected files are there

example_clip = dataset.choice_clip()  # choose a random example clip
print(example_clip)  # see the available data

See the documentation for more examples and the API reference.

@misc{fuentes_salamon2021soundata,
      title={Soundata: A Python library for reproducible use of audio datasets}, 
      author={Magdalena Fuentes and Justin Salamon and Pablo Zinemanas and Martín Rocamora and 
      Genís Plaja and Irán R. Román and Marius Miron and Xavier Serra and Juan Pablo Bello},
      year={2021},
      eprint={2109.12690},
      archivePrefix={arXiv},
      primaryClass={cs.SD}
}

When working with datasets, please cite the version of soundata that you are using AND include the reference of the dataset, which can be found in the respective dataset loader using the cite() method.

We welcome and encourage contributions to this library, especially new datasets. Please see contributing for guidelines.