| Specaugment: A simple data augmentation method for automatic speech recognition DS Park, W Chan, Y Zhang, CC Chiu, B Zoph, ED Cubuk, QV Le arXiv preprint arXiv:1904.08779, 2019 | 4092 | 2019 |
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| W2v-bert: Combining contrastive learning and masked language modeling for self-supervised speech pre-training YA Chung, Y Zhang, W Han, CC Chiu, J Qin, R Pang, Y Wu 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2021 | 383 | 2021 |
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| Pushing the limits of semi-supervised learning for automatic speech recognition Y Zhang, J Qin, DS Park, W Han, CC Chiu, R Pang, QV Le, Y Wu arXiv preprint arXiv:2010.10504, 2020 | 362 | 2020 |
| Advances in joint CTC-attention based end-to-end speech recognition with a deep CNN encoder and RNN-LM T Hori, S Watanabe, Y Zhang, W Chan arXiv preprint arXiv:1706.02737, 2017 | 356 | 2017 |
| Simple recurrent units for highly parallelizable recurrence T Lei, Y Zhang, SI Wang, H Dai, Y Artzi arXiv preprint arXiv:1709.02755, 2017 | 333 | 2017 |
| Contextnet: Improving convolutional neural networks for automatic speech recognition with global context W Han, Z Zhang, Y Zhang, J Yu, CC Chiu, J Qin, A Gulati, R Pang, Y Wu arXiv preprint arXiv:2005.03191, 2020 | 307 | 2020 |
| Hierarchical generative modeling for controllable speech synthesis WN Hsu, Y Zhang, RJ Weiss, H Zen, Y Wu, Y Wang, Y Cao, Y Jia, Z Chen, ... arXiv preprint arXiv:1810.07217, 2018 | 276 | 2018 |
| Improved noisy student training for automatic speech recognition DS Park, Y Zhang, Y Jia, W Han, CC Chiu, B Li, Y Wu, QV Le arXiv preprint arXiv:2005.09629, 2020 | 265 | 2020 |
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