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Summary:
Add badges of supported properties and devices to functionals and transforms.

This commit adds `.. devices::` and `.. properties::` directives to sphinx.

APIs with these directives will have badges (based off of shields.io) which link to the
page with description of these features.

Continuation of https://github.com/pytorch/audio/issues/2316
Excluded dtypes for further improvement, and actually added badges to most of functional/transforms.

Pull Request resolved: https://github.com/pytorch/audio/pull/2321

Reviewed By: hwangjeff

Differential Revision: D35489063

Pulled By: mthrok

fbshipit-source-id: f68a70ebb22df29d5e9bd171273bd19007a81762

Summary:
This commit adds tutorial for device ASR, and update API for device streaming.

The changes for the interface are
1. Add `timeout` and `backoff` parameters to `process_packet` and `stream` methods.
2. Move `fill_buffer` method to private.

When dealing with device stream, there are situations where the device buffer is not
ready and the system returns `EAGAIN`. In such case, the previous implementation of
`process_packet` method raised an exception in Python layer , but for device ASR,
this is inefficient. A better approach is to retry within C++ layer in blocking manner.
The new `timeout` parameter serves this purpose.

Pull Request resolved: https://github.com/pytorch/audio/pull/2202

Reviewed By: nateanl

Differential Revision: D34475829

Pulled By: mthrok

fbshipit-source-id: bb6d0b125d800f87d189db40815af06fbd4cab59

Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2177

Reviewed By: hwangjeff

Differential Revision: D33893052

Pulled By: nateanl

fbshipit-source-id: 00ff011eb96662b162c0327196a9564721e9c8f7

Summary:
* tutorial for streaming API https://541810-90321822-gh.circle-artifacts.com/0/docs/tutorials/streaming_api_tutorial.html
* tutorial for online speech recognition with Emformer RNN-T https://541810-90321822-gh.circle-artifacts.com/0/docs/tutorials/online_asr_tutorial.html

Pull Request resolved: https://github.com/pytorch/audio/pull/2193

Reviewed By: hwangjeff

Differential Revision: D33971312

Pulled By: mthrok

fbshipit-source-id: f9b69114255f15eaf4463ca85b3efb0ba321a95f

Summary:
This PR adds the prototype streaming API.
The implementation is based on ffmpeg libraries.

For the detailed usage, please refer to [the resulting tutorial](https://534376-90321822-gh.circle-artifacts.com/0/docs/tutorials/streaming_api_tutorial.html).

Pull Request resolved: https://github.com/pytorch/audio/pull/2164

Reviewed By: hwangjeff

Differential Revision: D33934457

Pulled By: mthrok

fbshipit-source-id: 92ade4aff2d25baf02c0054682d4fbdc9ba8f3fe

Summary:
Missed a couple of spots in https://github.com/pytorch/audio/issues/2187.

Pull Request resolved: https://github.com/pytorch/audio/pull/2189

Reviewed By: carolineechen, nateanl, mthrok

Differential Revision: D33926342

Pulled By: hwangjeff

fbshipit-source-id: e1324c0fe8f9be90ad3143d19cd61c3d53f02b06

Summary:
Regroup RNN-T components under `torchaudio.prototype.models` and `torchaudio.prototype.pipelines`.

Updated docs: https://492321-90321822-gh.circle-artifacts.com/0/docs/prototype.html

Pull Request resolved: https://github.com/pytorch/audio/pull/2110

Reviewed By: carolineechen, mthrok

Differential Revision: D33354116

Pulled By: hwangjeff

fbshipit-source-id: 9cf4afed548cb173d56211c16d31bcfa25a8e4cb

Summary:
### Change list

* Split the documentation of prototypes
* Add a new API reference section dedicated for prototypes.
* Hide the signature of KenLMLexiconDecoder constructor. (cc carolineechen )
  * https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.ctc_decoder.html#torchaudio.prototype.ctc_decoder.KenLMLexiconDecoder
* Hide the signature of RNNT constructor. (cc hwangjeff )
  * https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.rnnt.html#torchaudio.prototype.RNNT
* Tweak CTC tutorial
  * Replace hyperlinks to API reference with backlinks
  * Add `progress=False` to download

### Follow-up

RNNT decoder and CTC decode returns their own `Hypothesis` classes. When I tried to add Hypothesis of CTC decode to the documentation, the build process complains that it's ambiguous.
I think the Hypothesis classes can be put inside of each decoder. (if TorchScript supports it) or make the name different, but in that case the interface of each Hypothesis has to be generic enough.

### Before

https://pytorch.org/audio/main/prototype.html

<img width="1390" alt="Screen Shot 2021-12-28 at 1 05 53 PM" src="https://user-images.githubusercontent.com/855818/147594425-6c7f8126-ab76-4edc-a616-a00901e7e9ef.png">

### After

https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.html

<img width="1202" alt="Screen Shot 2021-12-28 at 8 37 35 PM" src="https://user-images.githubusercontent.com/855818/147619281-8152b1ae-e127-40b2-a944-dc11b114b629.png">

https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.rnnt.html

<img width="1415" alt="Screen Shot 2021-12-28 at 8 38 27 PM" src="https://user-images.githubusercontent.com/855818/147619331-077b55b5-c5e9-47ab-bfe6-873e41c738c8.png">

https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.ctc_decoder.html

<img width="1417" alt="Screen Shot 2021-12-28 at 8 39 04 PM" src="https://user-images.githubusercontent.com/855818/147619364-63df3457-a4b2-4223-973f-f4301bd45280.png">

Pull Request resolved: https://github.com/pytorch/audio/pull/2108

Reviewed By: hwangjeff, carolineechen, nateanl

Differential Revision: D33340816

Pulled By: mthrok

fbshipit-source-id: 870edfadbe41d6f8abaf78fdb7017b3980dfe187

Summary:
demonstrate usage of the CTC beam search decoder w/ lexicon constraint and KenLM support, on a LibriSpeech sample and using a pretrained wav2vec2 model

rendered: https://485200-90321822-gh.circle-artifacts.com/0/docs/tutorials/asr_inference_with_ctc_decoder_tutorial.html

follow-ups:
- incorporate `nbest`
- demonstrate customizability of different beam search parameters

Pull Request resolved: https://github.com/pytorch/audio/pull/2106

Reviewed By: mthrok

Differential Revision: D33340946

Pulled By: carolineechen

fbshipit-source-id: 0ab838375d96a035d54ed5b5bd9ab4dc8d19adb7

- Add link to index page on left
- Package Reference -> API Reference
- Update description.

* Refactor tutorial organization

* Merge tutorial subdirectoris under to examples/gallery/tutorials
* Do not use index.rst generated by Sphinx-gallery
* Instead use flat structure so that all the tutorials are listed in left menu
* Use `_assets` dir for artifacts of tutorials

- Move wav2vec2 pretrained weights to `torchaudio.pipelines` namespace to align with #1872.
- Split `Wav2Vec2PretrainedModelBundle` into `Wav2Vec2Bundle` (for pre-training model) and  `Wav2Vec2ASRBundle` (for models fine-tuned for ASR).
- Update base URL

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.

Replace the prototype RNNT implementation (using warp-transducer) with one without external library dependencies

Adds introductory context and links to the PyTorch Libraries to audio docs.

- Addresses #549 #638 #786 
- Add `torchaudio` top level module doc
- Separate `torchaudio` top level module doc from `index.html`
- Add `backend` module doc.
- Remove `-> None` from function signature as it adds noise to documentation
- Changed function argument name of `torchaudio.backend.sox_io_backend.save` from `tensor` to `src`, so that it matches with the reset of backends.
- Tweak bunch of docstrings

* Add sox_utils module

* Make init/shutdown thread safe

* Add sox effects implementation

* Add test for sox effects

* Update docstrings and add examples

Add Kaldi IO as a dependency + put  a wrapper to convert to Tensor + add test to check correct type (#111)