diff --git a/egs/librispeech/ASR/conformer_ctc/subsampling.py b/egs/librispeech/ASR/conformer_ctc/subsampling.py
index 97b9ae97b..e38a94d09 100644
--- a/egs/librispeech/ASR/conformer_ctc/subsampling.py
+++ b/egs/librispeech/ASR/conformer_ctc/subsampling.py
@@ -48,12 +48,12 @@ class Conv2dSubsampling(nn.Module):
                 in_channels=1, out_channels=odim, kernel_size=3, stride=2
             ),
             nn.ReLU(),
-            ExpScale(odim, 1, 1, speed=50.0),
+            ExpScale(odim, 1, 1, speed=20.0),
             nn.Conv2d(
                 in_channels=odim, out_channels=odim, kernel_size=3, stride=2
             ),
             nn.ReLU(),
-            ExpScale(odim, 1, 1, speed=50.0),
+            ExpScale(odim, 1, 1, speed=20.0),
         )
         self.out = nn.Linear(odim * (((idim - 1) // 2 - 1) // 2), odim)
         self.out_norm = nn.LayerNorm(odim, elementwise_affine=False)
diff --git a/egs/librispeech/ASR/transducer_stateless/conformer.py b/egs/librispeech/ASR/transducer_stateless/conformer.py
index dc6b54399..368165008 100644
--- a/egs/librispeech/ASR/transducer_stateless/conformer.py
+++ b/egs/librispeech/ASR/transducer_stateless/conformer.py
@@ -156,14 +156,14 @@ class ConformerEncoderLayer(nn.Module):
 
         self.feed_forward = nn.Sequential(
             nn.Linear(d_model, dim_feedforward),
-            ExpScaleSwish(dim_feedforward, speed=50.0),
+            ExpScaleSwish(dim_feedforward, speed=20.0),
             nn.Dropout(dropout),
             nn.Linear(dim_feedforward, d_model),
         )
 
         self.feed_forward_macaron = nn.Sequential(
             nn.Linear(d_model, dim_feedforward),
-            ExpScaleSwish(dim_feedforward, speed=50.0),
+            ExpScaleSwish(dim_feedforward, speed=20.0),
             nn.Dropout(dropout),
             nn.Linear(dim_feedforward, d_model),
         )
@@ -874,7 +874,7 @@ class ConvolutionModule(nn.Module):
             bias=bias,
         )
         # shape: (channels, 1), broadcasts with (batch, channel, time).
-        self.activation = ExpScaleSwish(channels, 1, speed=50.0)
+        self.activation = ExpScaleSwish(channels, 1, speed=20.0)
 
         self.pointwise_conv2 = nn.Conv1d(
             channels,