Tweak tutorials (#2630)

Summary:
Resolves the following warnings

```
/torchaudio/docs/source/tutorials/asr_inference_with_ctc_decoder_tutorial.rst:195: WARNING: Unexpected indentation.
/torchaudio/docs/source/tutorials/asr_inference_with_ctc_decoder_tutorial.rst:446: WARNING: Unexpected indentation.
/torchaudio/docs/source/tutorials/audio_io_tutorial.rst:559: WARNING: Content block expected for the "note" directive; none found.
/torchaudio/docs/source/tutorials/mvdr_tutorial.rst:338: WARNING: Bullet list ends without a blank line; unexpected unindent.
```

Pull Request resolved: https://github.com/pytorch/audio/pull/2630

Reviewed By: nateanl

Differential Revision: D38816632

Pulled By: mthrok

fbshipit-source-id: 135ded4e064d136be67ce24439e96f5e9c9ce635

examples/tutorials/asr_inference_with_ctc_decoder_tutorial.py

@@ -109,7 +109,9 @@ IPython.display.Audio(speech_file)
 
 ######################################################################
 # The transcript corresponding to this audio file is
-# ::
+#
+# .. code-block::
+#
 #    i really was very much afraid of showing him how much shocked i was at some parts of what he said
 #
 
@@ -139,7 +141,7 @@ if sample_rate != bundle.sample_rate:
 # file, where each line consists of the tokens corresponding to the same
 # index, or as a list of tokens, each mapping to a unique index.
 #
-# ::
+# .. code-block::
 #
 #    # tokens.txt
 #    _
@@ -162,7 +164,7 @@ print(tokens)
 # only words from the lexicon. The expected format of the lexicon file is
 # a line per word, with a word followed by its space-split tokens.
 #
-# ::
+# .. code-block::
 #
 #    # lexcion.txt
 #    a a |
@@ -283,7 +285,9 @@ greedy_decoder = GreedyCTCDecoder(tokens)
 # predicted token IDs, corresponding words (if a lexicon is provided), hypothesis score,
 # and timesteps corresponding to the token IDs. Recall the transcript corresponding to the
 # waveform is
-# ::
+#
+# .. code-block::
+#
 #    i really was very much afraid of showing him how much shocked i was at some parts of what he said
 #
 

examples/tutorials/mvdr_tutorial.py

@@ -219,6 +219,7 @@ stft_noise = stft(waveform_noise)
 # -  signal-to-distortion ratio (SDR)
 # -  scale-invariant signal-to-noise ratio (Si-SNR, or Si-SDR in some papers)
 # -  Perceptual Evaluation of Speech Quality (PESQ)
+#
 # We also evaluate the intelligibility of the speech with the Short-Time Objective Intelligibility
 # (STOI) metric.