Speech2TextTransformer
# What does this PR do?

This PR adds the S2T model from [fairseq](https://github.com/pytorch/fairseq/tree/master/examples/speech_to_text) for end-to-end ASR and Speech-Translation (ST).

The model architecture is somewhat similar to the mBART model, except
- the encoder contains the convolutional subsampling module to downsample the speech features.
- no token embeddings in encoder.

This PR also adds the `Speech2TextFeatureExtractor`, and `Speech2TextProcessor` classes analogous to `Wav2Vec2` extractor and processor.

The `Speech2TextFeatureExtractor` here has an extra dependency on `torchaudio` which is required for extracting fbank features

The `generate` method works out-of-the-box for S2T!  Usage example 

```python
 import torch
 from transformers import Speech2TextForConditionalGeneration, Speech2TextProcessor
 from datasets import load_dataset
 import soundfile as sf

 def map_to_array(batch):
     speech, _ = sf.read(batch["file"])
     batch["speech"] = speech
     return batch

ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
samples = ds.map(map_to_array)[5:8]

model = Speech2TextForConditionalGeneration.from_pretrained("valhalla/s2t_librispeech_small")
processor = Speech2TextProcessor.from_pretrained("valhalla/s2t_librispeech_small")

features = processor(samples["speech"], sampling_rate=16_000, padding=True, return_tensors="pt")
gen_tokens = model.generate(
    input_ids=features["input_features"],
    attention_mask=features["attention_mask"],
)
generated = processor.batch_decode(gen_tokens, skip_special_tokens=True)
```

TODOs:
- [x] add tests
- [x] implement `Speech2TextProcessor` after #10324 is merged
- [x] finish docs
- [ ] port and eval the CoVoST2 and MuSTc checkpoints
- [ ] add training/fine-tuning script in a follow-up PR

@patrickvonplaten, @sgugger , @LysandreJik  The PR is now finalized and ready for your review :) <|||||>I've added proper instructions to install the extra dependencies and addressed Patrick and Sylvain's comments regarding the docs and imports. All slow/non-slow tests are passing!

Merging!<|||||>Edit: please see this issue: #10631 <|||||>hi @xjdeng

Thanks for reporting this. This PR is now merged. So could you please open an issue with this error, we will discuss it there.
