Python library for loading and working with sound datasets.
Project description
soundata
Common loaders for 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
Installation
To install, simply run:
pip install soundata
Quick example
import soundata
urbansound8k = soundata.initialize('urbansound8k')
urbansound8k.download() # download the dataset
urbansound8k.validate() # validate that all the expected files are there
example_clip = urbansound8k.choice_clip() # choose a random example clip
print(example_clip) # see the available data
See the documentation for more examples and the API reference.
Currently supported datasets
- ESC-50
- FSD50K
- FSDnoisy18K
- TAU Urban Acoustic Scenes 2019
- TAU Urban Acoustic Scenes 2020 Mobile
- TUT Sound events 2017
- URBAN-SED
- UrbanSound8K
- More added soon!
For the complete list of supported datasets, see the documentation
Citing
TODO
paper
bibtex
When working with datasets, please cite the version of soundata that you are using (given by the DOI above) AND include the reference of the dataset,
which can be found in the respective dataset loader using the cite() method.
Contributing a new dataset loader
We welcome contributions to this library, especially new datasets. Please see contributing for guidelines.
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