| Superb: Speech processing universal performance benchmark S Yang, PH Chi, YS Chuang, CIJ Lai, K Lakhotia, YY Lin, AT Liu, J Shi, ... arXiv preprint arXiv:2105.01051, 2021 | 912 | 2021 |
| Mockingjay: Unsupervised speech representation learning with deep bidirectional transformer encoders AT Liu, S Yang, PH Chi, P Hsu, H Lee ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 452 | 2020 |
| Tera: Self-supervised learning of transformer encoder representation for speech AT Liu, SW Li, H Lee IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 2351-2366, 2021 | 400 | 2021 |
| SUPERB-SG: Enhanced speech processing universal performance benchmark for semantic and generative capabilities HS Tsai, HJ Chang, WC Huang, Z Huang, K Lakhotia, S Yang, S Dong, ... arXiv preprint arXiv:2203.06849, 2022 | 95 | 2022 |
| Adversarial defense for automatic speaker verification by cascaded self-supervised learning models H Wu, X Li, AT Liu, Z Wu, H Meng, H Lee ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 45 | 2021 |
| Qaner: Prompting question answering models for few-shot named entity recognition AT Liu, W Xiao, H Zhu, D Zhang, SW Li, A Arnold arXiv preprint arXiv:2203.01543, 2022 | 40 | 2022 |
| Understanding Self-Attention of Self-Supervised Audio Transformers S Yang, AT Liu, H Lee Proc. Interspeech 2020, and ICML 2020 Workshop on Self-supervision in Audio …, 2020 | 36 | 2020 |
| Defense for black-box attacks on anti-spoofing models by self-supervised learning H Wu, AT Liu, H Lee Proc. Interspeech 2020, International Speech Communication Association (ISCA), 2020 | 35 | 2020 |
| Improving the adversarial robustness for speaker verification by self-supervised learning H Wu, X Li, AT Liu, Z Wu, H Meng, HY Lee IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 202-217, 2021 | 34 | 2021 |
| Unsupervised end-to-end learning of discrete linguistic units for voice conversion AT Liu, P Hsu, H Lee Proc. Interspeech 2019, International Speech Communication Association (ISCA …, 2019 | 34 | 2019 |
| Towards robust neural vocoding for speech generation: A survey P Hsu, C Wang, AT Liu, H Lee arXiv preprint arXiv:1912.02461, 2019 | 30 | 2019 |
| Don't speak too fast: The impact of data bias on self-supervised speech models Y Meng, YH Chou, AT Liu, H Lee https://arxiv.org/pdf/2110.07957.pdf, 2021 | 24 | 2021 |
| A Large-Scale Evaluation of Speech Foundation Models S Yang, HJ Chang, Z Huang, AT Liu, CI Lai, H Wu, J Shi, X Chang, ... IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2024 | 11 | 2024 |
| S3prl: The self-supervised speech pre-training and representation learning toolkit AT Liu, Y Shu-wen online GitHub reposi-tory, 2020 | 7 | 2020 |
| Parallel synthesis for autoregressive speech generation P Hsu, D Liu, AT Liu, H Lee IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2023 | 4 | 2023 |
| On the social bias of speech self-supervised models YC Lin, TQ Lin, HC Lin, AT Liu, H Lee arXiv preprint arXiv:2406.04997, 2024 | 3 | 2024 |
| SUPERB: Speech processing Universal PERformance Benchmark.(2021) S Yang, PH Chi, YS Chuang, CIJ Lai, K Lakhotia, YY Lin, AT Liu, J Shi, ... arXiv preprint arXiv 2105, 2021 | 3 | 2021 |
| Dynamic-superb phase-2: A collaboratively expanding benchmark for measuring the capabilities of spoken language models with 180 tasks C Huang, WC Chen, S Yang, AT Liu, CA Li, YX Lin, WC Tseng, A Diwan, ... arXiv preprint arXiv:2411.05361, 2024 | 1 | 2024 |
| Representation Learning of Structured Data for Medical Foundation Models VP Dwivedi, V Schlegel, AT Liu, TT Nguyen, AR Kashyap, J Wei, WH Yin, ... arXiv preprint arXiv:2410.13351, 2024 | | 2024 |
| Efficient Training of Self-Supervised Speech Foundation Models on a Compute Budget AT Liu, YC Lin, H Wu, S Winkler, H Lee arXiv preprint arXiv:2409.16295, 2024 | | 2024 |
Hung-yi LeeNational Taiwan UniversityVerified email at ntu.edu.tw
