Datasets:
| license: cc-by-4.0 | |
| task_categories: | |
| - audio-classification | |
| - automatic-speech-recognition | |
| size_categories: | |
| - n<1K | |
| pretty_name: MIT Environmental Impulse Response Dataset | |
| # MIT Environmental Impulse Response Dataset | |
| The audio recordings in this dataset are originally created by the Computational Audition Lab at MIT. The source of the data can be found at: [https://mcdermottlab.mit.edu/Reverb/IR_Survey.html](https://mcdermottlab.mit.edu/Reverb/IR_Survey.html). | |
| This mirror provides the 16 kHz WAV files used for wake-word training augmentation in the Tater Totterson trainer projects. The files were resampled to 16 kHz to keep the dataset small and convenient for machine-learning audio pipelines. | |
| ## License | |
| This impulse-response dataset is released under the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/). | |
| ## Attribution | |
| Please cite the original paper when using this dataset: | |
| ```bibtex | |
| @article{traer2016naturalreverberation, | |
| doi = {10.1073/pnas.1612524113}, | |
| author = {Traer, James and McDermott, Josh H.}, | |
| title = {Statistics of natural reverberation enable perceptual separation of sound and space}, | |
| journal = {Proceedings of the National Academy of Sciences}, | |
| volume = {113}, | |
| number = {48}, | |
| pages = {E7856-E7865}, | |
| year = {2016}, | |
| url = {https://www.pnas.org/doi/abs/10.1073/pnas.1612524113} | |
| } | |
| ``` | |