Add EMFORMER_RNNT_BASE_MUSTC bundle to torchaudio.prototype (#2241)

Summary:
This PR provides a RNNTBundle that is pre-trained on the MuST-C release v2.0 dataset.
The model preserves the casing and punctuations of the transcripts when training the SentencePiece model.

Here is the model performance on the dev and test sets of MuST-C 2.0:
|                   |          WER |
|:-----------------:|-------------:|
| dev               |       0.190  |
| tst-COMMON        |       0.213  |
| tst-HE            |       0.186  |

Pull Request resolved: https://github.com/pytorch/audio/pull/2241

Reviewed By: mthrok

Differential Revision: D34267792

Pulled By: nateanl

fbshipit-source-id: 67bca9f277e66d41a4530d01615f249b3cec7167

docs/source/prototype.pipelines.rst

@@ -9,6 +9,14 @@ The pipelines subpackage contains APIs to models with pretrained weights and rel
 RNN-T Streaming/Non-Streaming ASR
 ---------------------------------
 
+EMFORMER_RNNT_BASE_MUSTC
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. container:: py attribute
+
+   .. autodata:: EMFORMER_RNNT_BASE_MUSTC
+      :no-value:
+
 EMFORMER_RNNT_BASE_TEDLIUM3
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 

torchaudio/prototype/pipelines/__init__.py

-from .rnnt_pipeline import EMFORMER_RNNT_BASE_TEDLIUM3
+from .rnnt_pipeline import EMFORMER_RNNT_BASE_MUSTC, EMFORMER_RNNT_BASE_TEDLIUM3
 
 
 __all__ = [
+    "EMFORMER_RNNT_BASE_MUSTC",
     "EMFORMER_RNNT_BASE_TEDLIUM3",
 ]

torchaudio/prototype/pipelines/rnnt_pipeline.py

@@ -4,6 +4,28 @@ from torchaudio.models import emformer_rnnt_base
 from torchaudio.pipelines import RNNTBundle
 
 
+EMFORMER_RNNT_BASE_MUSTC = RNNTBundle(
+    _rnnt_path="emformer_rnnt_base_mustc.pt",
+    _rnnt_factory_func=partial(emformer_rnnt_base, num_symbols=501),
+    _global_stats_path="global_stats_rnnt_mustc.json",
+    _sp_model_path="spm_bpe_500_mustc.model",
+    _right_padding=4,
+    _blank=500,
+    _sample_rate=16000,
+    _n_fft=400,
+    _n_mels=80,
+    _hop_length=160,
+    _segment_length=16,
+    _right_context_length=4,
+)
+EMFORMER_RNNT_BASE_MUSTC.__doc__ = """Pre-trained Emformer-RNNT-based ASR pipeline capable of performing both streaming and non-streaming inference.
+    The underlying model is constructed by :py:func:`torchaudio.models.emformer_rnnt_base`
+    and utilizes weights trained on MuST-C release v2.0 dataset using training script ``train.py``
+    `here <https://github.com/pytorch/audio/tree/main/examples/asr/emformer_rnnt>`__ with ``num_symbols=501``.
+    Please refer to :py:class:`torchaudio.pipelines.RNNTBundle` for usage instructions.
+    """
+
+
 EMFORMER_RNNT_BASE_TEDLIUM3 = RNNTBundle(
     _rnnt_path="emformer_rnnt_base_tedlium3.pt",
     _rnnt_factory_func=partial(emformer_rnnt_base, num_symbols=501),