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README.md

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 These are model weights originally provided by the authors of the paper [Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction](https://arxiv.org/pdf/2201.02184.pdf).
 
 Video recordings of speech contain correlated audio and visual information, providing a strong signal for speech representation learning from the speaker’s lip
-movements and the produced sound. Audio-Visual Hidden Unit BERT (AV-HuBERT), a self-supervised representation learning framework for
-audio-visual speech, which masks multi-stream video input and predicts automatically discovered and iteratively refined multimodal hidden units. AV-HuBERT
+movements and the produced sound. 
+
+Audio-Visual Hidden Unit BERT (AV-HuBERT), a self-supervised representation learning framework for audio-visual speech, which masks multi-stream video input and predicts automatically discovered and iteratively refined multimodal hidden units. AV-HuBERT
 learns powerful audio-visual speech representation benefiting both lip-reading and automatic speech recognition.
 
 ## Datasets