| SPIRAL: Self-supervised Perturbation-Invariant Representation Learning for Speech Pre-Training | |
| ======== | |
| This is the pretrained model of **SPIRAL Base with Multi-Condition Training**, trained with 960-hour LibriSpeech data, and noise dataset from [ICASSP 2021 DNS Challenge](https://github.com/microsoft/DNS-Challenge/tree/icassp2021-final) for noise robustness. | |
| Citation | |
| ======== | |
| If you find SPIRAL useful in your research, please cite the following paper: | |
| ``` | |
| @inproceedings{huang2022spiral, | |
| title={{SPIRAL}: Self-supervised Perturbation-Invariant Representation Learning for Speech Pre-Training}, | |
| author={Wenyong Huang and Zhenhe Zhang and Yu Ting Yeung and Xin Jiang and Qun Liu}, | |
| booktitle={International Conference on Learning Representations}, | |
| year={2022}, | |
| url={https://openreview.net/forum?id=TBpg4PnXhYH} | |
| } | |
| ``` |