Update CONTRIBUTING with doc conventions (#1898)

CONTRIBUTING.md

@@ -138,27 +138,37 @@ The built docs should now be available in `docs/build/html`
 ## Conventions
 
 As a good software development practice, we try to stick to existing variable
-names and shape (for tensors).
+names and shape (for tensors), and maintain consistent docstring standards.
 The following are some of the conventions that we follow.
 
-- We use an ellipsis "..." as a placeholder for the rest of the dimensions of a
+- Tensor
+  - We use an ellipsis "..." as a placeholder for the rest of the dimensions of a
     tensor, e.g. optional batching and channel dimensions. If batching, the
     "batch" dimension should come in the first diemension.
-- Tensors are assumed to have "channel" dimension coming before the "time"
+  - Tensors are assumed to have "channel" dimension coming before the "time"
     dimension. The bins in frequency domain (freq and mel) are assumed to come
     before the "time" dimension but after the "channel" dimension. These
     ordering makes the tensors consistent with PyTorch's dimensions.
-- For size names, the prefix `n_` is used (e.g. "a tensor of size (`n_freq`,
+  - For size names, the prefix `n_` is used (e.g. "a tensor of size (`n_freq`,
     `n_mels`)") whereas dimension names do not have this prefix (e.g. "a tensor of
     dimension (channel, time)")
+- Docstring
+  - Tensor dimensions are enclosed with single backticks.
+    ``waveform (Tensor): Tensor of audio of dimension `(..., time)` ``
+  - Parameter type for variable of type `T` with a default value: `(T, optional)`
+  - Parameter type for variable of type `Optional[T]`: `(T or None)`
+  - Return type for a tuple or list of known elements:
+    `(element1, element2)` or `[element1, element2]`
+  - Return type for a tuple or list with an arbitrary number of elements
+    of type T: `Tuple[T]` or `List[T]`
 
 Here are some of the examples of commonly used variables with thier names,
 meanings, and shapes (or units):
 
-* `waveform`: a tensor of audio samples with dimensions (..., channel, time)
-* `sample_rate`: the rate of audio dimensions (samples per second)
-* `specgram`: a tensor of spectrogram with dimensions (..., channel, freq, time)
-* `mel_specgram`: a mel spectrogram with dimensions (..., channel, mel, time)
+* `waveform`: a tensor of audio samples with dimensions `(..., channel, time)`
+* `sample_rate`: the rate of audio dimensions `(samples per second)`
+* `specgram`: a tensor of spectrogram with dimensions `(..., channel, freq, time)`
+* `mel_specgram`: a mel spectrogram with dimensions `(..., channel, mel, time)`
 * `hop_length`: the number of samples between the starts of consecutive frames
 * `n_fft`: the number of Fourier bins
 * `n_mels`, `n_mfcc`: the number of mel and MFCC bins