# SC09 Dataset

SC09 is a raw audio waveform dataset used in the paper "It's Raw! Audio Generation with State-Space Models". It was previously used as a challenging problem for unconditional audio generation by Donahue et al. (2019), and was originally introduced as a dataset for keyword spotting by Warden (2018). The SC09 dataset consists of 1s clips of utterances of the digits zero through nine across a variety of speakers, with diverse accents and noise conditions.

We include a single `sc09.zip` file that contains:
- folders `zero` through `nine`, each containing audio files sampled at 16kHz corresponding to utterances for the digit
- `validation_list.txt` containing the list of validation utterances
- `testing_list.txt` containing the list of testing utterances
- the original `LICENSE` file

We split the data into train-val-test for training SaShiMi models and baselines by following the splits provided in `validation_list.txt` and `testing_list.txt`.

You can use the following BibTeX entries to appropriately cite prior work related to this dataset if you decide to use this in your research:
```
@article{goel2022sashimi,
  title={It's Raw! Audio Generation with State-Space Models},
  author={Goel, Karan and Gu, Albert and Donahue, Chris and R\'{e}, Christopher},
  journal={arXiv preprint arXiv:xxxx.yyyyy},
  year={2022}
}

@inproceedings{donahue2019adversarial,
  title={Adversarial Audio Synthesis},
  author={Donahue, Chris and McAuley, Julian and Puckette, Miller},
  booktitle={International Conference on Learning Representations},
  year={2019}
}

@article{Warden2018SpeechCA,
  title={Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition},
  author={Pete Warden},
  journal={ArXiv},
  year={2018},
  volume={abs/1804.03209}
}
```