moderate amount of this data easily available. SpeechStew
(Chan et al., 2021) mixes together 7 pre-existing datasets
totalling 5,140 hours of supervision. While not insigniﬁ-
cant, this is still tiny compared to the previously mentioned
1,000,000 hours of unlabeled speech data utilized in Zhang
et al. (2021).
Recognizing the limiting size of existing high-quality super-
vised datasets, recent efforts have created larger datasets for
speech recognition. By relaxing the requirement of gold-
standard human-validated transcripts, Chen et al. (2021) and
Galvez et al. (2021) make use of sophisticated automated
RobustSpeechRecognitionviaLarge-ScaleWeakSupervision