diff --git a/egs/multi_zh_en/ASR/zipformer/multi_dataset.py b/egs/multi_zh_en/ASR/zipformer/multi_dataset.py
index d8b66609c..1bc514d61 100644
--- a/egs/multi_zh_en/ASR/zipformer/multi_dataset.py
+++ b/egs/multi_zh_en/ASR/zipformer/multi_dataset.py
@@ -15,6 +15,7 @@
 # limitations under the License.
 
 
+import argparse
 import logging
 from functools import lru_cache
 from pathlib import Path
@@ -24,14 +25,15 @@ from lhotse import CutSet, load_manifest_lazy
 
 
 class MultiDataset:
-    def __init__(self, fbank_dir: str):
+    def __init__(self, args: argparse.Namespace):
         """
         Args:
           manifest_dir:
             It is expected to contain the following files:
             - aishell2_cuts_train.jsonl.gz
         """
-        self.fbank_dir = Path(fbank_dir)
+        self.fbank_dir = Path(args.fbank_dir)
+        self.use_tal_csasr = args.use_tal_csasr
 
     def train_cuts(self) -> CutSet:
         logging.info("About to get multidataset train cuts")
@@ -42,11 +44,33 @@ class MultiDataset:
             self.fbank_dir / "aishell2_cuts_train.jsonl.gz"
         )
 
+        # TAL-CSASR
+        if self.use_tal_csasr:
+            logging.info("Loading TAL-CSASR in lazy mode")
+            tal_csasr_cuts = load_manifest_lazy(
+                self.fbank_dir / "tal_csasr_cuts_train_set.jsonl.gz"
+            )
+
         # LibriSpeech
         train_clean_100_cuts = self.train_clean_100_cuts()
         train_clean_360_cuts = self.train_clean_360_cuts()
         train_other_500_cuts = self.train_other_500_cuts()
 
+        if self.use_tal_csasr:
+            return CutSet.mux(
+                aishell_2_cuts,
+                train_clean_100_cuts,
+                train_clean_360_cuts,
+                train_other_500_cuts,
+                tal_csasr_cuts,
+                weights=[
+                    len(aishell_2_cuts),
+                    len(train_clean_100_cuts),
+                    len(train_clean_360_cuts),
+                    len(train_other_500_cuts),
+                    len(tal_csasr_cuts),
+                ],
+            )
         return CutSet.mux(
             aishell_2_cuts,
             train_clean_100_cuts,
@@ -99,7 +123,7 @@ class MultiDataset:
         # LibriSpeech
         test_clean_cuts = self.test_clean_cuts()
         test_other_cuts = self.test_other_cuts()
-        
+
         logging.info("Loading TAL-CSASR set in lazy mode")
         tal_csasr_cuts = load_manifest_lazy(
             self.fbank_dir / "tal_csasr_cuts_test_set.jsonl.gz"
diff --git a/egs/multi_zh_en/ASR/zipformer/train.py b/egs/multi_zh_en/ASR/zipformer/train.py
index 8318fc1ee..0fcb7e51e 100755
--- a/egs/multi_zh_en/ASR/zipformer/train.py
+++ b/egs/multi_zh_en/ASR/zipformer/train.py
@@ -468,6 +468,13 @@ def get_parser():
         help="Whether to use half precision training.",
     )
 
+    parser.add_argument(
+        "--use-tal-csasr",
+        type=str2bool,
+        default=False,
+        help="Whether to use TAL-CSASR training data.",
+    )
+
     add_model_arguments(parser)
 
     return parser