Spiking Speech Commands v0.2
The SSC dataset is a spiking version of the Speech Commands dataset release by Google (Speech Commands). SSC was generated using Lauscher, an artificial cochlea model. The SSC dataset consists of utterances recorded from a larger number of speakers under controlled conditions. Spikes were generated in 700 input channels, and it contains 35 word categories from a large number of speakers.
A full description of the dataset and how it was created can be found in the paper below. Please cite this paper if you make use of the dataset.
Cramer, B.; Stradmann, Y.; Schemmel, J.; and Zenke, F. "The Heidelberg Spiking Data Sets for the Systematic Evaluation of Spiking Neural Networks". IEEE Transactions on Neural Networks and Learning Systems 33, 2744–2757, 2022.
Variants: SSC
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Audio Classification | Event-SSM | Scalable Event-by-event Processing of Neuromorphic … | 2024-04-29 |
| Audio Classification | SNN with Dilated Convolution with Learnable Spacings | Learning Delays in Spiking Neural … | 2023-06-30 |
| Audio Classification | Adaptive SRNN | Accurate and efficient time-domain classification … | 2021-03-12 |
Recent papers with results on this dataset: