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license: apache-2.0 |
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language: |
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- en |
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pipeline_tag: automatic-speech-recognition |
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datasets: |
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- LRS3 |
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tags: |
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- Audio Visual to Text |
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- Automatic Speech Recognition |
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--- |
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## Model Description |
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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). |
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<figure> |
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<img src="https://huggingface.co/vumichien/AV-HuBERT/blob/main/HuBert.png" alt="Audio-visual HuBERT"> |
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<figcaption>Audio-visual HuBERT |
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</figcaption> |
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</figure> |
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Video recordings of speech contain correlated audio and visual information, providing a strong signal for speech representation learning from the speaker’s lip |
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movements and the produced sound. |
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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 |
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learns powerful audio-visual speech representation benefiting both lip-reading and automatic speech recognition. |
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## Datasets |
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The authors trained the model on lip-reading benchmark LRS3 datasets (433 hours). |
