diff --git a/egs/librispeech/ASR/conformer_mmi_phone/decode.py b/egs/librispeech/ASR/conformer_mmi_phone/decode.py
index 7e9c8f78e..6f485ba57 100755
--- a/egs/librispeech/ASR/conformer_mmi_phone/decode.py
+++ b/egs/librispeech/ASR/conformer_mmi_phone/decode.py
@@ -62,10 +62,15 @@ def get_parser():
         type=str,
     )
 
+    parser.add_argument(
+        "--num-paths",
+        type=int,
+    )
+
     parser.add_argument(
         "--lattice-score-scale",
         type=float,
-        default=1.0,
+        default=0.5,
         help="The scale to be applied to `lattice.scores`."
         "It's needed if you use any kinds of n-best based rescoring. "
         "Currently, it is used when the decoding method is: nbest, "
@@ -86,7 +91,7 @@ def get_params() -> AttributeDict:
             "nhead": 8,
             "attention_dim": 512,
             "subsampling_factor": 4,
-            "num_decoder_layers": 0,
+            "num_decoder_layers": 6,
             "vgg_frontend": False,
             "is_espnet_structure": True,
             "mmi_loss": False,
@@ -110,7 +115,6 @@ def get_params() -> AttributeDict:
             #  "method": "nbest-oracle",
             # num_paths is used when method is "nbest", "nbest-rescoring",
             # attention-decoder, and nbest-oracle
-            "num_paths": 100,
         }
     )
     return params
@@ -261,6 +265,8 @@ def decode_one_batch(
             memory=memory,
             memory_key_padding_mask=memory_key_padding_mask,
             scale=params.lattice_score_scale,
+            sos_id=params.sos_id,
+            eos_id=params.eos_id,
         )
     else:
         assert False, f"Unsupported decoding method: {params.method}"
@@ -474,10 +480,15 @@ def main():
         num_decoder_layers=params.num_decoder_layers,
         vgg_frontend=params.vgg_frontend,
         is_espnet_structure=params.is_espnet_structure,
-        mmi_loss=params.mmi_loss,
+        is_bpe=False,
         use_feat_batchnorm=params.use_feat_batchnorm,
     )
 
+    assert model.decoder_num_class == num_classes + 1
+
+    params.sos_id = num_classes
+    params.eos_id = num_classes
+
     if params.avg == 1:
         load_checkpoint(f"{params.exp_dir}/epoch-{params.epoch}.pt", model)
     else: