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Summary:
The PR move `SquimObjective` and `SquimSubjective` models and corresponding factory functions and pre-trained pipelines out of prototype and to the core directory. They will be included in the next official release.

Pull Request resolved: https://github.com/pytorch/audio/pull/3512

Reviewed By: mthrok

Differential Revision: D47837434

Pulled By: nateanl

fbshipit-source-id: d0639f29079f7e1afc30f236849e530c8cadffd8

Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3415

Differential Revision: D46526437

Pulled By: mthrok

fbshipit-source-id: f78d19c19d7e68f67712412de35d9ed50f47263b

Summary:
Add scatter plots for STOI, PESQ, Si-SDR, and MOS scores to demonstrate the performance of `SquimObjective` and `SquimSubjective` models and how close they are to the ground truths.

Pull Request resolved: https://github.com/pytorch/audio/pull/3313

Reviewed By: hwangjeff

Differential Revision: D45620311

Pulled By: nateanl

fbshipit-source-id: cb58ffd3744df4749b9385876da8de0cffd93557

Summary:
The PR adds a tutorial that demonstrates how to use pre-trained `TorchAudio-SQUIM` pipelines to estimate objective and subjective metric scores (PESQ, STOI, Si-SDR, MOS).

Pull Request resolved: https://github.com/pytorch/audio/pull/3279

Reviewed By: hwangjeff

Differential Revision: D45415404

Pulled By: nateanl

fbshipit-source-id: abcaeadcca0eabc2dca53b607eac6257a701c903