Web: http://arxiv.org/abs/2206.07627

June 16, 2022, 1:12 a.m. | Jan Lehečka, Jan Švec, Aleš Pražák, Josef V. Psutka

cs.CL updates on arXiv.org arxiv.org

In this paper, we present our progress in pretraining Czech monolingual audio
transformers from a large dataset containing more than 80 thousand hours of
unlabeled speech, and subsequently fine-tuning the model on automatic speech
recognition tasks using a combination of in-domain data and almost 6 thousand
hours of out-of-domain transcribed speech. We are presenting a large palette of
experiments with various fine-tuning setups evaluated on two public datasets
(CommonVoice and VoxPopuli) and one extremely challenging dataset from the
MALACH project. …

arxiv audio automatic speech recognition datasets large datasets speech speech recognition transformers

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