Karan Goel
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Add SC09 dataset readme.
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README.md
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# SC09 Dataset
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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.
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We include a single `sc09.zip` file that contains:
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- folders `zero` through `nine`, each containing audio files sampled at 16kHz corresponding to utterances for the digit
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- `validation_list.txt` containing the list of validation utterances
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- `testing_list.txt` containing the list of testing utterances
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- the original `LICENSE` file
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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`.
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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:
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```
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@article{goel2022sashimi,
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title={It's Raw! Audio Generation with State-Space Models},
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author={Goel, Karan and Gu, Albert and Donahue, Chris and R\'{e}, Christopher},
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journal={arXiv preprint arXiv:xxxx.yyyyy},
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year={2022}
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}
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@inproceedings{donahue2019adversarial,
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title={Adversarial Audio Synthesis},
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author={Donahue, Chris and McAuley, Julian and Puckette, Miller},
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booktitle={International Conference on Learning Representations},
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year={2019}
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}
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@article{Warden2018SpeechCA,
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title={Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition},
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author={Pete Warden},
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journal={ArXiv},
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year={2018},
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volume={abs/1804.03209}
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}
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```
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