diff --git a/egs/aishell/ASR/conformer_ctc/export.py b/egs/aishell/ASR/conformer_ctc/export.py
index 1df3cfdc2..49871d437 100755
--- a/egs/aishell/ASR/conformer_ctc/export.py
+++ b/egs/aishell/ASR/conformer_ctc/export.py
@@ -23,12 +23,12 @@ import argparse
 import logging
 from pathlib import Path
 
+import k2
 import torch
 from conformer import Conformer
 
 from icefall.checkpoint import average_checkpoints, load_checkpoint
-from icefall.lexicon import Lexicon
-from icefall.utils import AttributeDict, str2bool
+from icefall.utils import AttributeDict, num_tokens, str2bool
 
 
 def get_parser():
@@ -63,11 +63,10 @@ def get_parser():
     )
 
     parser.add_argument(
-        "--lang-dir",
+        "--tokens",
         type=str,
-        default="data/lang_char",
-        help="""It contains language related input files such as "lexicon.txt"
-        """,
+        required=True,
+        help="Path to the tokens.txt.",
     )
 
     parser.add_argument(
@@ -98,16 +97,16 @@ def get_params() -> AttributeDict:
 def main():
     args = get_parser().parse_args()
     args.exp_dir = Path(args.exp_dir)
-    args.lang_dir = Path(args.lang_dir)
 
     params = get_params()
     params.update(vars(args))
 
-    logging.info(params)
+    # Load tokens.txt here
+    token_table = k2.SymbolTable.from_file(params.tokens)
 
-    lexicon = Lexicon(params.lang_dir)
-    max_token_id = max(lexicon.tokens)
-    num_classes = max_token_id + 1  # +1 for the blank
+    num_classes = num_tokens(token_table) + 1  # +1 for the blank
+
+    logging.info(params)
 
     device = torch.device("cpu")
     if torch.cuda.is_available():