diff --git a/egs/tedlium2/ASR/conformer_ctc3/.train.py.swp b/egs/tedlium2/ASR/conformer_ctc3/.train.py.swp
index 09fef4cf4..9b802dc05 100644
Binary files a/egs/tedlium2/ASR/conformer_ctc3/.train.py.swp and b/egs/tedlium2/ASR/conformer_ctc3/.train.py.swp differ
diff --git a/egs/tedlium2/ASR/conformer_ctc3/train.py b/egs/tedlium2/ASR/conformer_ctc3/train.py
index 9ba5ca6b2..f6c1e4fd9 100755
--- a/egs/tedlium2/ASR/conformer_ctc3/train.py
+++ b/egs/tedlium2/ASR/conformer_ctc3/train.py
@@ -589,8 +589,8 @@ def compute_loss(
                 allow_truncate=params.subsampling_factor - 1,
             )
             
-            dense_fsa_vec2 = [
-                    k2.DenseFsaVec(
+            dense_fsa_vec_inter = [
+                k2.DenseFsaVec(
                     nnet_output[1][2],
                     supervision_segments,
                     allow_truncate=params.subsampling_factor - 1,
@@ -616,19 +616,25 @@ def compute_loss(
                     allow_truncate=params.subsampling_factor - 1,
                 )
             ]
-            ctc_loss = (1-params.interctc_weight)* k2.ctc_loss(
+
+            ctc_loss = k2.ctc_loss(
                 decoding_graph=decoding_graph,
                 dense_fsa_vec=dense_fsa_vec1,
                 output_beam=params.beam_size,
                 reduction=params.reduction,
                 use_double_scores=params.use_double_scores,
-            ) + params.interctc_weight * k2.ctc_loss(
-                decoding_graph=decoding_graph,
-                dense_fsa_vec=dense_fsa_vec2,
-                output_beam=params.beam_size,
-                reduction=params.reduction,
-                use_double_scores=params.use_double_scores,
-            )
+            ) 
+            
+            inter_ctc_loss = 0
+            for fsa in dense_fsa_vec_inter:
+                inter_ctc_loss += k2.ctc_loss(
+                    decoding_graph=decoding_graph,
+                    dense_fsa_vec=fsa,
+                    output_beam=params.beam_size,
+                    reduction=params.reduction,
+                    use_double_scores=params.use_double_scores,
+                ) 
+
 
         else:
             dense_fsa_vec = k2.DenseFsaVec(