| Dynamic-superb: Towards a dynamic, collaborative, and comprehensive instruction-tuning benchmark for speech C Huang, KH Lu, SH Wang, CY Hsiao, CY Kuan, H Wu, S Arora, ... ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 32 | 2024 |
| 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 | 3 | 2024 |
| ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets J Shi, SH Wang, W Chen, M Bartelds, VB Kumar, J Tian, X Chang, ... arXiv preprint arXiv:2406.08641, 2024 | 3 | 2024 |
| How to Learn a New Language? An Efficient Solution for Self-Supervised Learning Models Unseen Languages Adaption in Low-Resource Scenario SH Wang, ZC Chen, J Shi, MT Chuang, GT Lin, KP Huang, D Harwath, ... arXiv preprint arXiv:2411.18217, 2024 | 1 | 2024 |
| Fusion of Discrete Representations and Self-Augmented Representations for Multilingual Automatic Speech Recognition S Wang, J Shi, C Huang, S Watanabe, H Lee SLT 2024, 2024 | | 2024 |
| Systematic Analysis for Pretrained Language Model Priming for Parameter-Efficient Fine-tuning SC Huang, SH Wang, MH Shih, S Sahay, HY Lee Proceedings of the 2024 Conference of the North American Chapter of the …, 2024 | | 2024 |
| General Framework for Self-Supervised Model Priming for Parameter-Efficient Fine-tuning SC Huang, SH Wang, MH Shih, S Sahay, H Lee arXiv preprint arXiv:2212.01032, 2022 | | 2022 |
