diff --git a/funasr/bin/asr_infer.py b/funasr/bin/asr_infer.py
index f8736e93a..f6c5504b8 100644
--- a/funasr/bin/asr_infer.py
+++ b/funasr/bin/asr_infer.py
@@ -1640,7 +1640,7 @@ class Speech2TextSAASR:
         assert check_argument_types()
         
         # 1. Build ASR model
-        from funasr.modules.beam_search.beam_search_sa_asr import BeamSearch
+        from funasr.tasks.sa_asr import ASRTask
         scorers = {}
         asr_model, asr_train_args = ASRTask.build_model_from_file(
             asr_train_config, asr_model_file, cmvn_file, device
@@ -1682,6 +1682,7 @@ class Speech2TextSAASR:
         # 4. Build BeamSearch object
         # transducer is not supported now
         beam_search_transducer = None
+        from funasr.modules.beam_search.beam_search_sa_asr import BeamSearch
         
         weights = dict(
             decoder=1.0 - ctc_weight,
diff --git a/funasr/bin/sa_asr_train.py b/funasr/bin/sa_asr_train.py
new file mode 100755
index 000000000..67106cf48
--- /dev/null
+++ b/funasr/bin/sa_asr_train.py
@@ -0,0 +1,50 @@
+# -*- encoding: utf-8 -*-
+#!/usr/bin/env python3
+# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
+#  MIT License  (https://opensource.org/licenses/MIT)
+
+import os
+
+from funasr.tasks.sa_asr import ASRTask
+
+
+# for ASR Training
+def parse_args():
+    parser = ASRTask.get_parser()
+    parser.add_argument(
+        "--gpu_id",
+        type=int,
+        default=0,
+        help="local gpu id.",
+    )
+    args = parser.parse_args()
+    return args
+
+
+def main(args=None, cmd=None):
+    # for ASR Training
+    ASRTask.main(args=args, cmd=cmd)
+
+
+if __name__ == '__main__':
+    args = parse_args()
+
+    # setup local gpu_id
+    if args.ngpu > 0:
+        os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
+
+    # DDP settings
+    if args.ngpu > 1:
+        args.distributed = True
+    else:
+        args.distributed = False
+    assert args.num_worker_count == 1
+
+    # re-compute batch size: when dataset type is small
+    if args.dataset_type == "small":
+        if args.batch_size is not None and args.ngpu > 0:
+            args.batch_size = args.batch_size * args.ngpu
+        if args.batch_bins is not None and args.ngpu > 0:
+            args.batch_bins = args.batch_bins * args.ngpu
+
+    main(args=args)