Add LRS3 data preparation

[mpc001]

This PR adds a data preparation recipe that uses the ultra face detector to extract full-face video. The resulting video output is then used as input for training and evaluating RNNT-based models for automatic speech recognition (ASR), visual speech recognition (VSR), and audio-visual ASR (AV-ASR) on the LRS3 dataset.

This PR also updates the word error rate (WER) for AV-ASR LRS3 models and improves the code readability.

[pytorch-bot]

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❌ 3 New Failures

As of commit 6231cb1:

NEW FAILURES - The following jobs have failed:

• build (3.8) (gh)
• unittests-windows-cpu / windows-job (gh)
• unittests-windows-gpu / windows-job (gh)

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[mthrok]

The code looks fine, but IIUC, the preparation uses four different FFmpeg-related packages. torchvision, opencv, ffmpeg, torchaudio.

This might cause some subtle difference in the data processing.

[facebook-github-bot]

@mthrok has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

[facebook-github-bot]

This pull request was exported from Phabricator. Differential Revision: D46799748

[facebook-github-bot]

@mthrok merged this pull request in 77cdd16.

[github-actions]

Hey @mthrok.
You merged this PR, but labels were not properly added. Please add a primary and secondary label (See https://github.com/pytorch/audio/blob/main/.github/process_commit.py).

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