diff --git a/egs/fisher_swbd/s5/local/chain/run_blstm_6j.sh b/egs/fisher_swbd/s5/local/chain/run_blstm_6j.sh
index e1df22ede91..9810a03ee58 100644
--- a/egs/fisher_swbd/s5/local/chain/run_blstm_6j.sh
+++ b/egs/fisher_swbd/s5/local/chain/run_blstm_6j.sh
@@ -1,4 +1,6 @@
 #!/bin/bash
+# Copyright 2017 University of Chinese Academy of Sciences (UCAS) Gaofeng Cheng
+# Apache 2.0
 
 # The model training procedure is similar to run_blstm_6j.sh under egs/swbd/s5c
 
diff --git a/egs/fisher_swbd/s5/local/chain/run_tdnn_lstm_1a.sh b/egs/fisher_swbd/s5/local/chain/run_tdnn_lstm_1a.sh
index 81af4a128e8..d057470552f 100644
--- a/egs/fisher_swbd/s5/local/chain/run_tdnn_lstm_1a.sh
+++ b/egs/fisher_swbd/s5/local/chain/run_tdnn_lstm_1a.sh
@@ -1,5 +1,10 @@
 #!/bin/bash
-# same as run_tdnn_opgru_1a.sh, but replacing Norm-OPGRU with LSTMP.
+# Copyright 2017 University of Chinese Academy of Sciences (UCAS) Gaofeng Cheng
+# Apache 2.0
+
+# Same as run_tdnn_opgru_1a.sh, but replacing Norm-OPGRU with LSTMP.
+# Also Batchnorm in TDNN layers does not reduce the WER in Fisher+SWBD, so in run_tdnn_lstm_1a.sh,
+# I just apply renorm component in TDNN layers.
 # ./local/chain/compare_wer_general.sh --looped tdnn_lstm_1a_sp
 # System                tdnn_lstm_1a_sp
 # WER on eval2000(tg)        12.3
@@ -15,7 +20,7 @@
 # Final train prob (xent)        -0.882
 # Final valid prob (xent)       -0.9393
 
-# ./show_chain_wer.sh tdnn_lstm_1b_sp
+# ./show_chain_wer.sh tdnn_lstm_1a_sp
 # %WER 16.0 | 2628 21594 | 86.3 9.0 4.7 2.3 16.0 54.4 | exp/chain/tdnn_lstm_1a_sp/decode_eval2000_fsh_sw1_tg/score_7_0.0/eval2000_hires.ctm.callhm.filt.sys
 # %WER 12.3 | 4459 42989 | 89.4 7.1 3.5 1.7 12.3 49.8 | exp/chain/tdnn_lstm_1a_sp/decode_eval2000_fsh_sw1_tg/score_8_0.0/eval2000_hires.ctm.filt.sys
 # %WER 8.4 | 1831 21395 | 92.7 5.1 2.2 1.1 8.4 42.3 | exp/chain/tdnn_lstm_1a_sp/decode_eval2000_fsh_sw1_tg/score_10_0.0/eval2000_hires.ctm.swbd.filt.sys
@@ -23,7 +28,7 @@
 # %WER 12.1 | 4459 42989 | 89.6 6.9 3.5 1.7 12.1 49.2 | exp/chain/tdnn_lstm_1a_sp/decode_eval2000_fsh_sw1_fg/score_8_0.0/eval2000_hires.ctm.filt.sys
 # %WER 8.2 | 1831 21395 | 93.1 5.1 1.8 1.3 8.2 41.7 | exp/chain/tdnn_lstm_1a_sp/decode_eval2000_fsh_sw1_fg/score_8_0.0/eval2000_hires.ctm.swbd.filt.sys
 
-# ./show_chain_wer_rt03.sh tdnn_lstm_1b_sp
+# ./show_chain_wer_rt03.sh tdnn_lstm_1a_sp
 # %WER 9.6 | 3970 36721 | 91.5 5.5 3.0 1.1 9.6 41.2 | exp/chain/tdnn_lstm_1a_sp/decode_rt03_fsh_sw1_tg/score_7_0.0/rt03_hires.ctm.fsh.filt.sys
 # %WER 11.6 | 8420 76157 | 89.7 6.8 3.4 1.4 11.6 43.0 | exp/chain/tdnn_lstm_1a_sp/decode_rt03_fsh_sw1_tg/score_7_0.0/rt03_hires.ctm.filt.sys
 # %WER 13.3 | 4450 39436 | 88.0 7.4 4.6 1.3 13.3 44.5 | exp/chain/tdnn_lstm_1a_sp/decode_rt03_fsh_sw1_tg/score_9_0.0/rt03_hires.ctm.swbd.filt.sys
diff --git a/egs/fisher_swbd/s5/local/chain/run_tdnn_opgru_1a.sh b/egs/fisher_swbd/s5/local/chain/run_tdnn_opgru_1a.sh
index e819a987a48..2de8d774451 100644
--- a/egs/fisher_swbd/s5/local/chain/run_tdnn_opgru_1a.sh
+++ b/egs/fisher_swbd/s5/local/chain/run_tdnn_opgru_1a.sh
@@ -1,4 +1,6 @@
 #!/bin/bash
+# Copyright 2017 University of Chinese Academy of Sciences (UCAS) Gaofeng Cheng
+# Apache 2.0
 
 # This is based on TDNN_LSTM_1b (from egs/swbd/s5c), but using the NormOPGRU to replace the LSTMP,
 # and adding chunk-{left,right}-context-initial=0