A Large-Scale Evaluation of Speech Foundation Models

The foundation model paradigm leverages a shared foundation model to achieve state-of-the-art (SOTA) performance for various tasks, requiring minimal downstream-specific data collection and modeling. This approach has proven crucial in the field of Natural Language Processing (NLP). However, the spe...

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Veröffentlicht in:	IEEE/ACM transactions on audio, speech, and language processing speech, and language processing, 2024, Vol.32, p.2884-2899
Hauptverfasser:	Yang, Shu-wen, Chang, Heng-Jui, Huang, Zili, Liu, Andy T., Lai, Cheng-I, Wu, Haibin, Shi, Jiatong, Chang, Xuankai, Tsai, Hsiang-Sheng, Huang, Wen-Chin, Feng, Tzu-hsun, Chi, Po-Han, Lin, Yist Y., Chuang, Yung-Sung, Huang, Tzu-Hsien, Tseng, Wei-Cheng, Lakhotia, Kushal, Li, Shang-Wen, Mohamed, Abdelrahman, Watanabe, Shinji, Lee, Hung-yi
Format:	Artikel
Sprache:	eng
Schlagworte:	Analytical models benchmark Benchmark testing Benchmarks Biological system modeling Computational modeling evaluation foundation model Information flow Natural language processing Protocols representation learning self-supervised learning Speech Speech processing Task analysis task generalization
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