6 citations · 15 across the 15 of their papers we have counts for
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cs.CL2023★ 1 cited
A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature Extractors
Shuyue Stella Li, Beining Xu, Xiangyu Zhang +3
In this work, we study the features extracted by English self-supervised learning (SSL) models in cross-lingual contexts and propose a new metric to predict the quality of feature…
cs.CL2023★ 1 cited
Generative error correction for code-switching speech recognition using large language models
Chen Chen, Yuchen Hu, Chao-Han Huck Yang +3
Code-switching (CS) speech refers to the phenomenon of mixing two or more languages within the same sentence. Despite the recent advances in automatic speech recognition (ASR), CS-…