diff --git a/egs/librispeech/ASR/conformer_ctc2/.train.py.swp b/egs/librispeech/ASR/conformer_ctc2/.train.py.swp
index 0877c9d6e..9e8e4b1da 100644
Binary files a/egs/librispeech/ASR/conformer_ctc2/.train.py.swp and b/egs/librispeech/ASR/conformer_ctc2/.train.py.swp differ
diff --git a/egs/librispeech/ASR/conformer_ctc2/train.py b/egs/librispeech/ASR/conformer_ctc2/train.py
index 3577d538a..2c2ea6192 100755
--- a/egs/librispeech/ASR/conformer_ctc2/train.py
+++ b/egs/librispeech/ASR/conformer_ctc2/train.py
@@ -641,7 +641,7 @@ def compute_loss(
             
             ctc_loss = (1-params.interctc_weight) * ctc_loss + params.interctc_weight * inter_ctc_loss
         
-        if (params.condition and params.group_num > 0) or (params.interctc and params.group_num > 0) or (params.group_num > 0):
+        if (params.condition and params.group_num > 0) or (params.interctc and params.group_num > 0):
             dense_fsa_vec = k2.DenseFsaVec(
                 nnet_output[0],
                 supervision_segments,
@@ -676,7 +676,22 @@ def compute_loss(
                 )
 
             ctc_loss = (1-params.interctc_weight) * ctc_loss + params.interctc_weight * inter_ctc_loss
-
+        
+        if not params.interctc and not params.condition and params.group_num > 0:
+            dense_fsa_vec = k2.DenseFsaVec(
+                nnet_output[0],
+                supervision_segments,
+                allow_truncate=params.subsampling_factor - 1,
+            )
+            
+            ctc_loss = k2.ctc_loss(
+                decoding_graph=decoding_graph,
+                dense_fsa_vec=dense_fsa_vec,
+                output_beam=params.beam_size,
+                reduction=params.reduction,
+                use_double_scores=params.use_double_scores,
+            ) 
+            
         if not params.interctc and not params.condition and params.group_num == 0:
             dense_fsa_vec = k2.DenseFsaVec(
                 nnet_output,