gigaspeech decode

egs/gigaspeech/ASR/pruned_transducer_stateless2/decode.py

@@ -74,6 +74,7 @@ from beam_search import (
     greedy_search_batch,
     modified_beam_search,
 )
+from gigaspeech_scoring import asr_text_post_processing
 from train import get_params, get_transducer_model
 
 from icefall.checkpoint import (
@@ -200,6 +201,17 @@ def get_parser():
     return parser
 
 
+def post_processing(
+    results: List[Tuple[List[str], List[str]]],
+) -> List[Tuple[List[str], List[str]]]:
+    new_results = []
+    for ref, hyp in results:
+        new_ref = asr_text_post_processing(' '.join(ref)).split()
+        new_hyp = asr_text_post_processing(' '.join(hyp)).split()
+        new_results.append((new_ref, new_hyp))
+    return new_results
+
+
 def decode_one_batch(
     params: AttributeDict,
     model: nn.Module,
@@ -354,10 +366,7 @@ def decode_dataset(
     except TypeError:
         num_batches = "?"
 
-    if params.decoding_method == "greedy_search":
-        log_interval = 100
-    else:
-        log_interval = 2
+    log_interval = 100
 
     results = defaultdict(list)
     for batch_idx, batch in enumerate(dl):
@@ -401,6 +410,7 @@ def save_results(
         recog_path = (
             params.res_dir / f"recogs-{test_set_name}-{key}-{params.suffix}.txt"
         )
+        results = post_processing(results)
         store_transcripts(filename=recog_path, texts=results)
         logging.info(f"The transcripts are stored in {recog_path}")
 

egs/gigaspeech/ASR/pruned_transducer_stateless2/gigaspeech_scoring.py

@@ -0,0 +1 @@
+../conformer_ctc/gigaspeech_scoring.py