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Summary:
This PR adds ``mvdr_weights_souden`` method to ``torchaudio.functional``.
It computes the MVDR weight matrix based on the solution proposed by [``Souden et, al.``](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.725.673&rep=rep1&type=pdf).
The input arguments are the complex-valued power spectral density (PSD) matrix of the target speech, PSD matrix of noise, int or one-hot Tensor to indicate the reference channel, respectively.

Pull Request resolved: https://github.com/pytorch/audio/pull/2228

Reviewed By: mthrok

Differential Revision: D34474018

Pulled By: nateanl

fbshipit-source-id: 725df812f8f6e6cc81cc37e8c3cb0da2ab3b74fb

Summary:
Adds implementation of Conformer module.

Adapted from sravyapopuri388's implementation for fairseq at https://github.com/fairinternal/fairseq-py/pull/2770.

Pull Request resolved: https://github.com/pytorch/audio/pull/2068

Reviewed By: mthrok

Differential Revision: D33236957

Pulled By: hwangjeff

fbshipit-source-id: 382d99394996ff5249522b5899e1a4b4a95de9e6

Future work items:
- length computation of GriffinLim
- better way to make InverseMelScale work in inference_mode

Adds an implementation of Emformer, a memory-efficient transformer architecture 
introduced in https://ieeexplore.ieee.org/document/9414560 that targets low-latency 
streaming speech recognition applications.

This commit adds the following HuBERT model architectures

 - `base` (pre-training)
 - `large` (pre-training / fine-tuning)
 - `xlarge` (pre-training / fine-tuning)

Since the internal components are same as `Wav2Vec2Model`, it reuses the existing modules..
With these models, it is possible to 
- import the pre-trained model published by `fairseq` and TorchScript it.
- fine-tune the existing model for downstream task.

Porting Tacotron2 from https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechSynthesis/Tacotron2/tacotron2/model.py

* Use `bibtex` for paper citations.
  * add `override.css` for fixing back reference.
  * wav2vec2
  * wav2letter
  * convtasnet
  * deepspeech
  * rnnt-loss
  * griffinlim
* Fix broken references in `filtering`.
* Fix note in soundfile backends.
* Tweak wav2vec2 example.
* Removes unused `pytorch_theme.css`