Findings of the 2023 ML-Superb Challenge: Pre-Training And Evaluation Over More Languages And Beyond
Author:
Affiliation:
1. Carnegie Mellon University, National Taiwan University
2. National Taiwan University
3. Renmin University of China
4. Meta AI
5. Rembrand
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10388490/10389614/10389628.pdf?arnumber=10389628
Reference58 articles.
1. Self-Supervised Speech Representation Learning: A Review
2. SUPERB: Speech Processing Universal PERformance Benchmark
3. wav2vec 2.0: A framework for self-supervised learning of speech representations;Baevski;Proc. NeurIPS,2020
4. HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
5. XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale
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