Datasets
Open Access
Heidelberg Spiking Datasets
- Citation Author(s):
-
JohannesSchemmel
FriedemannZenke - Submitted by:
- Friedemann Zenke
- Last updated:
- Tue, 05/17/2022 - 22:21
- DOI:
- 10.21227/51gn-m114
- Data Format:
- Link to Paper:
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Abstract
The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format. SHD as well as SSC are released under the Creative Commons Attribution 4.0 International License.
We provide two distinct classification datasets for spiking neural networks. | Name | Classes | Samples (train/valid/test) | Parent dataset | URL | | ---- | ------- | ------ | ------------------------- | --- | | SHD | 20 | 8332/-/2088 | Heidelberg Digits (HD) | https://compneuro.net/datasets/hd_audio.tar.gz | | SSC | 35 | 75466/9981/20382 | Speech Commands v0.2 | https://arxiv.org/abs/1804.03209 | Both datasets are based on respective audio datasets. Spikes in 700 input channels were generated using an artificial cochlea model. The SHD consists of approximately 10000 high-quality aligned studio recordings of spoken digits from 0 to 9 in both German and English language. Recordings exist of 12 distinct speakers two of which are only present in the test set. The SSC is based on the Speech Commands release by Google which consists of utterances recorded from a larger number of speakers under less controlled conditions. It contains 35 word categories from a larger number of speakers.
Dataset Files
Heidelberg Digits audio files hd_audio.tar.gz (321.44 MB)- Spiking Heidelberg Digits test set shd_test.h5.gz (36.37 MB)
- Spiking Heidelberg Digits training set shd_train.h5.gz (124.78 MB)
- Spiking Speech Commands training set ssc_train.h5.gz (1.11 GB)
- Spiking Speech Commands validation set ssc_valid.h5.gz (148.34 MB)
- Spiking Speech Commands test set ssc_test.h5.gz (308.34 MB)
- load_data_example.ipynb.gz (67.87 kB)
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Documentation
| Attachment | Size |
|---|---|
 Readme file with example Python code | 4.88 KB |
Comments
How can I reconfigure spiking context on another database? if possible, Which are the steps?