Minor fixes.

egs/librispeech/ASR/conformer_ctc/decode.py

@@ -326,20 +326,31 @@ def save_results(
     test_set_name: str,
     results_dict: Dict[str, List[Tuple[List[int], List[int]]]],
 ):
+    if params.method == "attention-decoder":
+        # Set it to False since there are too many logs.
+        enable_log = False
+    else:
+        enable_log = True
     test_set_wers = dict()
     for key, results in results_dict.items():
         recog_path = params.exp_dir / f"recogs-{test_set_name}-{key}.txt"
         store_transcripts(filename=recog_path, texts=results)
-        logging.info(f"The transcripts are stored in {recog_path}")
+        if enable_log:
+            logging.info(f"The transcripts are stored in {recog_path}")
 
         # The following prints out WERs, per-word error statistics and aligned
         # ref/hyp pairs.
         errs_filename = params.exp_dir / f"errs-{test_set_name}-{key}.txt"
         with open(errs_filename, "w") as f:
-            wer = write_error_stats(f, f"{test_set_name}-{key}", results)
+            wer = write_error_stats(
+                f, f"{test_set_name}-{key}", results, enable_log=enable_log
+            )
             test_set_wers[key] = wer
 
-        logging.info("Wrote detailed error stats to {}".format(errs_filename))
+        if enable_log:
+            logging.info(
+                "Wrote detailed error stats to {}".format(errs_filename)
+            )
 
     test_set_wers = sorted(test_set_wers.items(), key=lambda x: x[1])
     errs_info = params.exp_dir / f"wer-summary-{test_set_name}.txt"

egs/librispeech/ASR/local/compile_hlg.py

@@ -45,7 +45,7 @@ def compile_HLG(lang_dir: str) -> k2.Fsa:
         logging.info("Loading G_3_gram.fst.txt")
         with open("data/lm/G_3_gram.fst.txt") as f:
             G = k2.Fsa.from_openfst(f.read(), acceptor=False)
-            torch.save(G.as_dict(), "G_3_gram.pt")
+            torch.save(G.as_dict(), "data/lm/G_3_gram.pt")
 
     first_token_disambig_id = lexicon.token_table["#0"]
     first_word_disambig_id = lexicon.word_table["#0"]

icefall/utils.py

@@ -225,7 +225,10 @@ def store_transcripts(
 
 
 def write_error_stats(
-    f: TextIO, test_set_name: str, results: List[Tuple[str, str]]
+    f: TextIO,
+    test_set_name: str,
+    results: List[Tuple[str, str]],
+    enable_log: bool = True,
 ) -> float:
     """Write statistics based on predicted results and reference transcripts.
 
@@ -255,6 +258,9 @@ def write_error_stats(
       results:
         An iterable of tuples. The first element is the reference transcript
         while the second element is the predicted result.
+      enable_log:
+        If True, also print detailed WER to the console.
+        Otherwise, it is written only to the given file.
     Returns:
       Return None.
     """
@@ -290,11 +296,12 @@ def write_error_stats(
     tot_errs = sub_errs + ins_errs + del_errs
     tot_err_rate = "%.2f" % (100.0 * tot_errs / ref_len)
 
-    logging.info(
-        f"[{test_set_name}] %WER {tot_errs / ref_len:.2%} "
-        f"[{tot_errs} / {ref_len}, {ins_errs} ins, "
-        f"{del_errs} del, {sub_errs} sub ]"
-    )
+    if enable_log:
+        logging.info(
+            f"[{test_set_name}] %WER {tot_errs / ref_len:.2%} "
+            f"[{tot_errs} / {ref_len}, {ins_errs} ins, "
+            f"{del_errs} del, {sub_errs} sub ]"
+        )
 
     print(f"%WER = {tot_err_rate}", file=f)
     print(