Update CTC decoder docs (#2443)

Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2443

Reviewed By: nateanl

Differential Revision: D36909822

Pulled By: carolineechen

fbshipit-source-id: ef3ab2345e7a4666cf29dd02c83d03504e8aa62c

torchaudio/models/decoder/_ctc_decoder.py

@@ -27,7 +27,7 @@ _PretrainedFiles = namedtuple("PretrainedFiles", ["lexicon", "tokens", "lm"])
 
 
 class CTCHypothesis(NamedTuple):
-    r"""Represents hypothesis generated by CTC beam search decoder :py:func`CTCDecoder`.
+    r"""Represents hypothesis generated by CTC beam search decoder :py:func:`CTCDecoder`.
 
     :ivar torch.LongTensor tokens: Predicted sequence of token IDs. Shape `(L, )`, where
         `L` is the length of the output sequence
@@ -46,15 +46,14 @@ class CTCDecoder:
     """
     .. devices:: CPU
 
-    Lexically contrained CTC beam search decoder from *Flashlight* [:footcite:`kahn2022flashlight`].
+    CTC beam search decoder from *Flashlight* [:footcite:`kahn2022flashlight`].
 
     Note:
-        To build the decoder, please use factory function
-        :py:func:`ctc_decoder`.
+        To build the decoder, please use the factory function :py:func:`ctc_decoder`.
 
     Args:
         nbest (int): number of best decodings to return
-        lexicon (Dict or None): lexicon mapping of words to spellings, or None for lexicon free decoder
+        lexicon (Dict or None): lexicon mapping of words to spellings, or None for lexicon-free decoder
         word_dict (_Dictionary): dictionary of words
         tokens_dict (_Dictionary): dictionary of tokens
         lm (_LM): language model
@@ -211,12 +210,11 @@ def ctc_decoder(
     unk_word: str = "<unk>",
 ) -> CTCDecoder:
     """
-    Builds lexically constrained CTC beam search decoder from
-    *Flashlight* [:footcite:`kahn2022flashlight`].
+    Builds CTC beam search decoder from *Flashlight* [:footcite:`kahn2022flashlight`].
 
     Args:
         lexicon (str or None): lexicon file containing the possible words and corresponding spellings.
-            Each line consists of a word and its space separated spelling. If `None`, uses lexicon free
+            Each line consists of a word and its space separated spelling. If `None`, uses lexicon-free
             decoding.
         tokens (str or List[str]): file or list containing valid tokens. If using a file, the expected
             format is for tokens mapping to the same index to be on the same line
@@ -224,7 +222,7 @@ def ctc_decoder(
         nbest (int, optional): number of best decodings to return (Default: 1)
         beam_size (int, optional): max number of hypos to hold after each decode step (Default: 50)
         beam_size_token (int, optional): max number of tokens to consider at each decode step.
-            If None, it is set to the total number of tokens (Default: None)
+            If `None`, it is set to the total number of tokens (Default: None)
         beam_threshold (float, optional): threshold for pruning hypothesis (Default: 50)
         lm_weight (float, optional): weight of language model (Default: 2)
         word_score (float, optional): word insertion score (Default: 0)