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Summary:
This PR adds ``rtf_power`` method to ``torchaudio.functional``.
The method computes the relative transfer function (RTF) or the steering vector by [the power iteration method](https://onlinelibrary.wiley.com/doi/abs/10.1002/zamm.19290090206).
[This paper](https://arxiv.org/pdf/2011.15003.pdf) describes the power iteration method in English.
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, number of iterations, respectively.

Pull Request resolved: https://github.com/pytorch/audio/pull/2231

Reviewed By: mthrok

Differential Revision: D34474503

Pulled By: nateanl

fbshipit-source-id: 47011427ec4373f808755f0e8eff1efca57655eb

Summary:
This PR adds `rtf_evd` method to `torchaudio.functional`.
The method computes the relative transfer function (RTF) or the steering vector by eigenvalue decomposition.
The input argument is the power spectral density (PSD) matrix of the target speech.

Pull Request resolved: https://github.com/pytorch/audio/pull/2230

Reviewed By: mthrok

Differential Revision: D34474188

Pulled By: nateanl

fbshipit-source-id: 888df4b187608ed3c2b7271b34d2231cdabb0134

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

Pull Request resolved: https://github.com/pytorch/audio/pull/2229

Reviewed By: mthrok

Differential Revision: D34474119

Pulled By: nateanl

fbshipit-source-id: 2d6f62cd0858f29ed6e4e03c23dcc11c816204e2

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:
This PR adds ``psd`` method to ``torchaudio.functional``.
It computes the power spectral density (PSD) matrix of the complex-valued spectrum.
The method also supports normalization of Time-Frequency mask.

Pull Request resolved: https://github.com/pytorch/audio/pull/2227

Reviewed By: mthrok

Differential Revision: D34473908

Pulled By: nateanl

fbshipit-source-id: c1cfc584085d77881b35d41d76d39b26fca1dda9

* Add basic filtfilt implementation

* Add filtfilt to functional package; add tests
Co-authored-by: V G <vladislav.goncharenko@phystech.edu>

- Renamed torchaudio.functional.create_fb_matrix to torchaudio.functional.melscale_fbanks.
- Added interface with a warning for create_fb_matrix

Summary:
- Add linear_fbank method
- Add LFCC in transforms

* 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`

This PR additionally adds batching to kaldi compliance resample interface.

* Add griffinlim and DB_to_amplitude
* Fix Dataset docstring
* Fix other formatting
Co-authored-by: krishnakalyan3 <skalyan@cloudera.com>

* `istft` has been migrated to `pytorch`, and `torchaudio.functional.istft` has been deprecated in 0.6.0 release. This PR removes it
Co-authored-by: Jeremy Chen <jeremyyy@fb.com>

* Add bass with biquad

* Update functional.py

Add the normalization coefficients

* Update test_sox_compatibility.py

In test_sox_compatibility.py file, I add two bass tests: one test sets gain = 30, atol = 1e-4, the other sets gain = 40, atol = 1.5e-4. The details can be seen in pytorch#676

* Update torchscript_consistency_impl.py

Add torchscript test

* Add flake8 test
Co-authored-by: Ji Chen <jimchen90@devfair0160.h2.fair>

* Add flanger to functional
Signed-off-by: Bhargav Kathivarapu <bhargavkathivarapu31@gmail.com>

* Add random seed
Signed-off-by: Bhargav Kathivarapu <bhargavkathivarapu31@gmail.com>

* fix flanger
Signed-off-by: Bhargav Kathivarapu <bhargavkathivarapu31@gmail.com>

* shape

* Change bool arguments to strings
Signed-off-by: Bhargav Kathivarapu <bhargavkathivarapu31@gmail.com>

* Refactor tests
Signed-off-by: Bhargav Kathivarapu <bhargavkathivarapu31@gmail.com>
Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

Signed-off-by: Bhargav Kathivarapu <bhargavkathivarapu31@gmail.com>

* initial test, stub function, transform and docstring

* add draft working implementation, update docstrings

* merge VadSate into Vad calss, move Channel into Vad class

* remove functional stub for vad

* add wav file for test

* refactor _measure() to improve performance

* rename argument

* replace copy_ with assignment

* refactor init, update documentation, update test for readability

* clean up default values

* move code from transforms.py to funtional.py and integrate state into a function

* remove Channel state class

* fix calcuation of a flush point

* make multiple channels work

* clean up multi-channel, update test

* rename variables and re-org arguments for _measure

* fix linting errors

* add torchscript consistency test and fix errors

* support and test batch consistency, fix normalization

* update documentation, switch torchscript consistancy test to use transform to improve coverage

* fix linting errors

* remove un-used imports

* address PR comments

* add doc references into rst

* formatting.

* update datasets.

* Add overdrive to functional

* Minor change to overdrive

* Minor change to overdrive

* minor flake8 changes

* changes to make overdrive generic
Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

* Add dcshift to functional

* Doc string change and remove inplace clamp

* Minor Fix to dcshit and separate sox test refactoring

* Minor change to limiter_gain type

* adding dcshift to __all__ in functional

* add cmvn

* Update transforms.rst

add cmvn

* Correct the format

* Correct the format

* Correct the format

* add test unit and cmvn change to cmn

* fix bug
Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

* Add contrast to functional

* add tests for contrast and update functional.rst

* Minor changes to sox and batch tests for contrast

* sync docs with functionals.

* Adding transforms to documentations. Moving augmentations in transforms.

* Add basic low pass filtering
* Add highpass filtering
* More tests of IIR vs FIR
* Implement convolve function, add tests
* Move lfilter and convolve into functional, more tests
* added additional documentation for convolve and lfilter, renamed functional_filtering to functional_sox_convenience
* Follow naming convention for sample rate in functional
* fix failing vctk manifest test to account for adding more test audios into assets
* Adding documentation for lfilter, biquad, highpass_biquad, lowpass_biquad
* added matrix based implementation of lfilter
* adding python lfilter implementation
* factor out biquad, lowpass, highpass to sox compatibility