diff --git a/egs/gigaspeech/ASR/conformer_ctc/decode.py b/egs/gigaspeech/ASR/conformer_ctc/decode.py
index ec5854660..a810bef06 100755
--- a/egs/gigaspeech/ASR/conformer_ctc/decode.py
+++ b/egs/gigaspeech/ASR/conformer_ctc/decode.py
@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 # Copyright 2021 Xiaomi Corporation (Author: Liyong Guo, Fangjun Kuang)
+# Copyright 2022 Johns Hopkins University (Author: Guanbo Wang)
 #
 # See ../../../../LICENSE for clarification regarding multiple authors
 #
@@ -28,6 +29,7 @@ import torch
 import torch.nn as nn
 from asr_datamodule import GigaSpeechAsrDataModule
 from conformer import Conformer
+from gigaspeech_scoring import asr_text_post_processing
 
 from icefall.bpe_graph_compiler import BpeCtcTrainingGraphCompiler
 from icefall.checkpoint import average_checkpoints, load_checkpoint
@@ -170,6 +172,17 @@ def get_params() -> AttributeDict:
     return params
 
 
+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))
+        new_hyp = asr_text_post_processing(" ".join(hyp))
+        new_results.append((new_ref, new_hyp))
+    return new_results
+
+
 def decode_one_batch(
     params: AttributeDict,
     model: nn.Module,
@@ -488,7 +501,7 @@ def decode_dataset(
 def save_results(
     params: AttributeDict,
     test_set_name: str,
-    results_dict: Dict[str, List[Tuple[List[int], List[int]]]],
+    results_dict: Dict[str, List[Tuple[List[str], List[str]]]],
 ):
     if params.method == "attention-decoder":
         # Set it to False since there are too many logs.
@@ -498,6 +511,7 @@ def save_results(
     test_set_wers = dict()
     for key, results in results_dict.items():
         recog_path = params.exp_dir / f"recogs-{test_set_name}-{key}.txt"
+        results = post_processing(results)
         store_transcripts(filename=recog_path, texts=results)
         if enable_log:
             logging.info(f"The transcripts are stored in {recog_path}")
diff --git a/egs/gigaspeech/ASR/conformer_ctc/gigaspeech_scoring.py b/egs/gigaspeech/ASR/conformer_ctc/gigaspeech_scoring.py
new file mode 100755
index 000000000..ef53b77f8
--- /dev/null
+++ b/egs/gigaspeech/ASR/conformer_ctc/gigaspeech_scoring.py
@@ -0,0 +1,115 @@
+#!/usr/bin/env python3
+# Copyright 2021 Jiayu Du
+# Copyright 2022 Johns Hopkins University (Author: Guanbo Wang)
+#
+# See ../../../../LICENSE for clarification regarding multiple authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import argparse
+import os
+
+conversational_filler = [
+    "UH",
+    "UHH",
+    "UM",
+    "EH",
+    "MM",
+    "HM",
+    "AH",
+    "HUH",
+    "HA",
+    "ER",
+    "OOF",
+    "HEE",
+    "ACH",
+    "EEE",
+    "EW",
+]
+unk_tags = ["<UNK>", "<unk>"]
+gigaspeech_punctuations = [
+    "<COMMA>",
+    "<PERIOD>",
+    "<QUESTIONMARK>",
+    "<EXCLAMATIONPOINT>",
+]
+gigaspeech_garbage_utterance_tags = ["<SIL>", "<NOISE>", "<MUSIC>", "<OTHER>"]
+non_scoring_words = (
+    conversational_filler
+    + unk_tags
+    + gigaspeech_punctuations
+    + gigaspeech_garbage_utterance_tags
+)
+
+
+def asr_text_post_processing(text: str) -> str:
+    # 1. convert to uppercase
+    text = text.upper()
+
+    # 2. remove hyphen
+    #   "E-COMMERCE" -> "E COMMERCE", "STATE-OF-THE-ART" -> "STATE OF THE ART"
+    text = text.replace("-", " ")
+
+    # 3. remove non-scoring words from evaluation
+    remaining_words = []
+    for word in text.split():
+        if word in non_scoring_words:
+            continue
+        remaining_words.append(word)
+
+    return " ".join(remaining_words)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="This script evaluates GigaSpeech ASR result via"
+        "SCTK's tool sclite"
+    )
+    parser.add_argument(
+        "ref",
+        type=str,
+        help="sclite's standard transcription(trn) reference file",
+    )
+    parser.add_argument(
+        "hyp",
+        type=str,
+        help="sclite's standard transcription(trn) hypothesis file",
+    )
+    parser.add_argument(
+        "work_dir",
+        type=str,
+        help="working dir",
+    )
+    args = parser.parse_args()
+
+    if not os.path.isdir(args.work_dir):
+        os.mkdir(args.work_dir)
+
+    REF = os.path.join(args.work_dir, "REF")
+    HYP = os.path.join(args.work_dir, "HYP")
+    RESULT = os.path.join(args.work_dir, "RESULT")
+
+    for io in [(args.ref, REF), (args.hyp, HYP)]:
+        with open(io[0], "r", encoding="utf8") as fi:
+            with open(io[1], "w+", encoding="utf8") as fo:
+                for line in fi:
+                    line = line.strip()
+                    if line:
+                        cols = line.split()
+                        text = asr_text_post_processing(" ".join(cols[0:-1]))
+                        uttid_field = cols[-1]
+                        print(f"{text} {uttid_field}", file=fo)
+
+    # GigaSpeech's uttid comforms to swb
+    os.system(f"sclite -r {REF} trn -h {HYP} trn -i swb | tee {RESULT}")