Karan Goel commited on
Commit
a6309b4
1 Parent(s): 154880b

Add SC09 dataset readme.

Browse files
Files changed (1) hide show
  1. README.md +36 -0
README.md ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # SC09 Dataset
2
+
3
+ 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.
4
+
5
+ We include a single `sc09.zip` file that contains:
6
+ - folders `zero` through `nine`, each containing audio files sampled at 16kHz corresponding to utterances for the digit
7
+ - `validation_list.txt` containing the list of validation utterances
8
+ - `testing_list.txt` containing the list of testing utterances
9
+ - the original `LICENSE` file
10
+
11
+ 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`.
12
+
13
+ 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:
14
+ ```
15
+ @article{goel2022sashimi,
16
+ title={It's Raw! Audio Generation with State-Space Models},
17
+ author={Goel, Karan and Gu, Albert and Donahue, Chris and R\'{e}, Christopher},
18
+ journal={arXiv preprint arXiv:xxxx.yyyyy},
19
+ year={2022}
20
+ }
21
+
22
+ @inproceedings{donahue2019adversarial,
23
+ title={Adversarial Audio Synthesis},
24
+ author={Donahue, Chris and McAuley, Julian and Puckette, Miller},
25
+ booktitle={International Conference on Learning Representations},
26
+ year={2019}
27
+ }
28
+
29
+ @article{Warden2018SpeechCA,
30
+ title={Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition},
31
+ author={Pete Warden},
32
+ journal={ArXiv},
33
+ year={2018},
34
+ volume={abs/1804.03209}
35
+ }
36
+ ```