add timit w2vu recipe (#1991)

Summary:
## What does this PR do?
Add TIMIT data preparation scripts for wav2vec-U

Pull Request resolved: fairinternal/fairseq-py#1991

Reviewed By: alexeib

Differential Revision: D29284481

Pulled By: wnhsu

fbshipit-source-id: dccd75159a9de4f3cd95f9e4a90ce4bdf9264f2b

Author: Wei-Ning Hsu

examples/wav2vec/unsupervised/README.md

@@ -48,6 +48,16 @@ The fifth argument is which phonemizer to use. Supported values are [espeak](htt
 
 Pre-trained fasttext LID models can be downloaded [here](https://fasttext.cc/docs/en/language-identification.html).
 
+### Prepare TIMIT data
+TIMIT transcripts include silence. Therefore VAD is not used for audio preprocessing, and we do not wrap transcripts with silences or insert random silence in between words.
+
+To prepare TIMIT data for both the matched an unmatched setup:
+```shell
+bash scripts/prepare_timit.sh /dir/to/timit/raw/data /output/dir /path/to/wav2vec2/model.pt
+```
+
+Note that we assume the TIMIT distribution with capitalized directories and filenames are used (e.g., `TRAIN/DR1/FCJF0/SA1.PHN`).
+
 ## Generative adversarial training (GAN)
 
 We then use a GAN model to build a first unsupervised ASR model. The data preparation above of both speech features and text data is a necessary procedure that enables the generator to match speech to text in an unsupervised way. 

examples/wav2vec/unsupervised/config/timit_matched/test.uid

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