diff --git a/fluid/DeepASR/data_utils/augmentor/tests/test_data_trans.py b/fluid/DeepASR/data_utils/augmentor/tests/test_data_trans.py
index 9f76a9f8590d5f148398c4ffaff77dc95421df83..6b18f3fa5958a9e44899b39b1f583311f186f72e 100644
--- a/fluid/DeepASR/data_utils/augmentor/tests/test_data_trans.py
+++ b/fluid/DeepASR/data_utils/augmentor/tests/test_data_trans.py
@@ -8,6 +8,7 @@ import numpy as np
 import data_utils.augmentor.trans_mean_variance_norm as trans_mean_variance_norm
 import data_utils.augmentor.trans_add_delta as trans_add_delta
 import data_utils.augmentor.trans_splice as trans_splice
+import data_utils.augmentor.trans_delay as trans_delay
 
 
 class TestTransMeanVarianceNorm(unittest.TestCase):
@@ -112,5 +113,24 @@ class TestTransSplict(unittest.TestCase):
                         self.assertAlmostEqual(feature[i][j * 10 + k], cur_val)
 
 
+class TestTransDelay(unittest.TestCase):
+    """unittest TransDelay
+    """
+
+    def test_perform(self):
+        label = np.zeros((10, 1), dtype="int64")
+        for i in xrange(10):
+            label[i][0] = i
+
+        trans = trans_delay.TransDelay(5)
+        (_, label, _) = trans.perform_trans((None, label, None))
+
+        for i in xrange(5):
+            self.assertAlmostEqual(label[i + 5][0], i)
+
+        for i in xrange(5):
+            self.assertAlmostEqual(label[i][0], 0)
+
+
 if __name__ == '__main__':
     unittest.main()
diff --git a/fluid/DeepASR/data_utils/augmentor/trans_delay.py b/fluid/DeepASR/data_utils/augmentor/trans_delay.py
new file mode 100644
index 0000000000000000000000000000000000000000..b782498edfd5443806a6c80e3b4fe91b8e2b1cc9
--- /dev/null
+++ b/fluid/DeepASR/data_utils/augmentor/trans_delay.py
@@ -0,0 +1,37 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+import math
+
+
+class TransDelay(object):
+    """ Delay label, and copy first label value in the front. 
+        Attributes:
+            _delay_time : the delay frame num of label 
+    """
+
+    def __init__(self, delay_time):
+        """init construction
+            Args:
+                delay_time : the delay frame num of label
+        """
+        self._delay_time = delay_time
+
+    def perform_trans(self, sample):
+        """ 
+            Args:
+                sample(object):input sample, contain feature numpy and label numpy, sample name list
+            Returns:
+                (feature, label, name)
+        """
+        (feature, label, name) = sample
+
+        shape = label.shape
+        assert len(shape) == 2
+        label[self._delay_time:shape[0]] = label[0:shape[0] - self._delay_time]
+        for i in xrange(self._delay_time):
+            label[i][0] = label[self._delay_time][0]
+
+        return (feature, label, name)
diff --git a/fluid/DeepASR/train.py b/fluid/DeepASR/train.py
index be99998c8aa7f88d49dab711e94dcd7cfef042d6..50ca04702deeac3a915de01894733262c9f290d5 100644
--- a/fluid/DeepASR/train.py
+++ b/fluid/DeepASR/train.py
@@ -12,6 +12,7 @@ import paddle.fluid as fluid
 import data_utils.augmentor.trans_mean_variance_norm as trans_mean_variance_norm
 import data_utils.augmentor.trans_add_delta as trans_add_delta
 import data_utils.augmentor.trans_splice as trans_splice
+import data_utils.augmentor.trans_delay as trans_delay
 import data_utils.async_data_reader as reader
 from data_utils.util import lodtensor_to_ndarray
 from model_utils.model import stacked_lstmp_model
@@ -171,7 +172,7 @@ def train(args):
     ltrans = [
         trans_add_delta.TransAddDelta(2, 2),
         trans_mean_variance_norm.TransMeanVarianceNorm(args.mean_var),
-        trans_splice.TransSplice()
+        trans_splice.TransSplice(), trans_delay.TransDelay(5)
     ]
 
     feature_t = fluid.LoDTensor()