| Fastdiff: A fast conditional diffusion model for high-quality speech synthesis R Huang, MWY Lam, J Wang, D Su, D Yu, Y Ren, Z Zhao arXiv preprint arXiv:2204.09934, 2022 | 169 | 2022 |
| BDDM: Bilateral denoising diffusion models for fast and high-quality speech synthesis MWY Lam, J Wang, D Su, D Yu arXiv preprint arXiv:2203.13508, 2022 | 145* | 2022 |
| Development of the CUHK Dysarthric Speech Recognition System for the UA Speech Corpus. J Yu, X Xie, S Liu, S Hu, MWY Lam, X Wu, KH Wong, X Liu, H Meng Interspeech, 2938-2942, 2018 | 68 | 2018 |
| Efficient neural music generation MWY Lam, Q Tian, T Li, Z Yin, S Feng, M Tu, Y Ji, R Xia, M Ma, X Song, ... Advances in Neural Information Processing Systems 36, 2024 | 56 | 2024 |
| Sandglasset: A light multi-granularity self-attentive network for time-domain speech separation MWY Lam, J Wang, D Su, D Yu ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 56 | 2021 |
| Gaussian process lstm recurrent neural network language models for speech recognition MWY Lam, X Chen, S Hu, J Yu, X Liu, H Meng ICASSP 2019-2019 IEEE international conference on acoustics, speech and …, 2019 | 40 | 2019 |
| Effective low-cost time-domain audio separation using globally attentive locally recurrent networks MWY Lam, J Wang, D Su, D Yu 2021 IEEE Spoken Language Technology Workshop (SLT), 801-808, 2021 | 35 | 2021 |
| One-match-ahead forecasting in two-team sports with stacked Bayesian regressions MWY Lam Journal of Artificial Intelligence and Soft Computing Research 8 (3), 159-171, 2018 | 33 | 2018 |
| QuaRL: Quantization for fast and environmentally sustainable reinforcement learning S Krishnan, M Lam, S Chitlangia, Z Wan, G Barth-Maron, A Faust, ... arXiv preprint arXiv:1910.01055, 2019 | 29 | 2019 |
| Mixup-breakdown: a consistency training method for improving generalization of speech separation models MWY Lam, J Wang, D Su, D Yu ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 22 | 2020 |
| Benchmarking TinyML systems: Challenges and direction. arXiv CR Banbury, VJ Reddi, M Lam, W Fu, A Fazel, J Holleman, X Huang, ... arXiv preprint arXiv:2003.04821, 2020 | 16 | 2020 |
| Bayesian and gaussian process neural networks for large vocabulary continuous speech recognition S Hu, MWY Lam, X Xie, S Liu, J Yu, X Wu, X Liu, H Meng ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 16 | 2019 |
| Foundation models for music: A survey Y Ma, A Øland, A Ragni, BMS Del Sette, C Saitis, C Donahue, C Lin, ... arXiv preprint arXiv:2408.14340, 2024 | 12 | 2024 |
| LF-MMI Training of Bayesian and Gaussian Process Time Delay Neural Networks for Speech Recognition. S Hu, X Xie, S Liu, MWY Lam, J Yu, X Wu, X Liu, H Meng Interspeech, 2793-2797, 2019 | 11 | 2019 |
| Gaussian Process Neural Networks for Speech Recognition. MWY Lam, S Hu, X Xie, S Liu, J Yu, R Su, X Liu, H Meng INTERSPEECH, 1778-1782, 2018 | 11 | 2018 |
| Comparative Study of Parametric and Representation Uncertainty Modeling for Recurrent Neural Network Language Models. J Yu, MWY Lam, S Hu, X Wu, X Li, Y Cao, X Liu, H Meng Interspeech, 3510-3514, 2019 | 9 | 2019 |
| Training method and device for audio separation network, audio separation method and device, and medium J Wang, WY Lam, D Su, D Yu US Patent App. 17/682,399, 2022 | 8 | 2022 |
| Raw waveform encoder with multi-scale globally attentive locally recurrent networks for end-to-end speech recognition MWY Lam, J Wang, C Weng, D Su, D Yu arXiv preprint arXiv:2106.04275, 2021 | 8 | 2021 |
| Extract, Adapt and Recognize: An End-to-End Neural Network for Corrupted Monaural Speech Recognition. MWY Lam, J Wang, X Liu, H Meng, D Su, D Yu INTERSPEECH, 2778-2782, 2019 | 8 | 2019 |
| Tune-in: Training under negative environments with interference for attention networks simulating cocktail party effect J Wang, MWY Lam, D Su, D Yu Proceedings of the AAAI Conference on Artificial Intelligence 35 (16), 13961 …, 2021 | 7 | 2021 |
J WangPeking UniversityVerified email at tencent.com