Loss Prediction: End-to-End Active Learning for Speech Recognition

End-to-end speech recognition systems usually require huge amounts of labeling resource, while annotating the speech data is complicated and expensive. Active learning is the solution by selecting the most valuable samples for annotation.

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Jian Luo, Jianzong Wang, Ning Cheng, Jing Xiao (2024). Dataset: Loss Prediction: End-to-End Active Learning for Speech Recognition. https://doi.org/10.57702/rkewt7on

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2107.04289
Author Jian Luo
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Jianzong Wang
Ning Cheng
Jing Xiao