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Pseudo Label Is Better Than Human Label
[article]
2022
arXiv
pre-print
State-of-the-art automatic speech recognition (ASR) systems are trained with tens of thousands of hours of labeled speech data. Human transcription is expensive and time consuming. Factors such as the quality and consistency of the transcription can greatly affect the performance of the ASR models trained with these data. In this paper, we show that we can train a strong teacher model to produce high quality pseudo labels by utilizing recent self-supervised and semi-supervised learning
arXiv:2203.12668v3
fatcat:cgcqnldibva5fk2w6jcbstey34