A Large-Scale Evaluation of Speech Foundation Models-Reference-Cited by-同舟云学术

A Large-Scale Evaluation of Speech Foundation Models

Published:2024 Issue: Volume:32 Page:2884-2899
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Yang Shu-wen¹^ORCID,Chang Heng-Jui²^ORCID,Huang Zili³^ORCID,Liu Andy T.¹^ORCID,Lai Cheng-I²^ORCID,Wu Haibin¹^ORCID,Shi Jiatong⁴^ORCID,Chang Xuankai⁴^ORCID,Tsai Hsiang-Sheng¹^ORCID,Huang Wen-Chin⁵^ORCID,Feng Tzu-hsun¹^ORCID,Chi Po-Han¹^ORCID,Lin Yist Y.¹^ORCID,Chuang Yung-Sung²^ORCID,Huang Tzu-Hsien¹,Tseng Wei-Cheng¹^ORCID,Lakhotia Kushal⁶,Li Shang-Wen⁷^ORCID,Mohamed Abdelrahman⁶,Watanabe Shinji⁴^ORCID,Lee Hung-yi¹^ORCID

Affiliation:

1. Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan

2. CSAIL, MIT, Cambridge, MA, USA

3. CLSP, JHU, Baltimore, MD, USA

4. LTI, CMU, Pittsburgh, PA, USA

5. Graduate School of Informatics, Nagoya University, Nagoya, Aichi, Japan

6. FAIR, Menlo Park, CA, USA

7. Amazon AI, New York, NY, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570655/10304349/10502279.pdf?arnumber=10502279

Reference109 articles.

1. On the opportunities and risks of foundation models;Bommasani,2021

2. RoBERTa: A robustly optimized BERT pretraining approach;Liu,2019

3. An Unsupervised Autoregressive Model for Speech Representation Learning

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