diff --git a/egs/material/s5/local/rnnlm/run_tdnn_lstm.sh b/egs/material/s5/local/rnnlm/run_tdnn_lstm.sh
index c541a2f660b..3576aa54953 100755
--- a/egs/material/s5/local/rnnlm/run_tdnn_lstm.sh
+++ b/egs/material/s5/local/rnnlm/run_tdnn_lstm.sh
@@ -15,7 +15,6 @@
 
 # Begin configuration section.
 
-dir=exp/rnnlm_lstm_1a
 embedding_dim=512
 lstm_rpd=128
 lstm_nrpd=128
@@ -24,20 +23,25 @@ train_stage=-10
 
 # variables for lattice rescoring
 run_rescore=true
-ac_model_dir=exp/chain/tdnn_lstm1a_sp_ld5
+ac_model_dir=exp/$language/chain/tdnn_lstm1a_sp_ld5
 decode_dir_suffix=rnnlm_1a
 ngram_order=4 # approximate the lattice-rescoring by limiting the max-ngram-order
               # if it's set, it merges histories in the lattice if they share
               # the same ngram history and this prevents the lattice from 
               # exploding exponentially
 pruned_rescore=true
+language=swahili
 
 . ./cmd.sh
 . ./utils/parse_options.sh
 
-text=data/train/text
-lexicon=data/local/dict_nosp/lexiconp.txt
-text_dir=data/rnnlm/text_nosp_1e
+dir=exp/$language/rnnlm_lstm_1a
+
+text=data/$language/train/text
+lexicon=data/$language/local/dict_nosp/lexiconp.txt
+text_dir=data/$language/rnnlm/text_nosp_1e
+dir=exp/$language/rnnlm_lstm_1a
+
 mkdir -p $dir/config
 set -e
 
diff --git a/egs/material/s5_tagalog/local/rnnlm/run_tdnn_lstm.sh b/egs/material/s5_tagalog/local/rnnlm/run_tdnn_lstm.sh
deleted file mode 100755
index 877569c3501..00000000000
--- a/egs/material/s5_tagalog/local/rnnlm/run_tdnn_lstm.sh
+++ /dev/null
@@ -1,121 +0,0 @@
-#!/bin/bash
-
-# Copyright 2012  Johns Hopkins University (author: Daniel Povey)
-#           2017  Hainan Xu
-
-# This script trains LMs on the swbd LM-training data.
-
-# rnnlm/train_rnnlm.sh: best iteration (out of 10) was 3, linking it to final iteration.
-# rnnlm/train_rnnlm.sh: train/dev perplexity was 65.0 / 106.6.
-# Train objf: -5.17 -4.66 -4.37 -4.17 -3.99 -3.82 -3.66 -3.52 -3.39 -3.27 
-# Dev objf:   -9.55 -5.02 -4.73 -4.67 -4.69 -4.77 -4.90 -5.02 -5.16 -5.29 
-
-# %WER 46.51 [ 29942 / 64382, 3413 ins, 9336 del, 17193 sub ] exp/chain/tdnn_lstm1a_sp_ld5/decode_dev/wer_9_0.5
-# %WER 44.67 [ 28762 / 64382, 3276 ins, 9266 del, 16220 sub ] exp/chain/tdnn_lstm1a_sp_ld5/decode_dev_rnnlm_1a/wer_9_0.5
-
-# Begin configuration section.
-
-dir=exp/rnnlm_lstm_1a
-embedding_dim=256
-lstm_rpd=64
-lstm_nrpd=64
-stage=-10
-train_stage=-10
-
-# variables for lattice rescoring
-run_rescore=true
-ac_model_dir=exp/chain/tdnn_lstm1a_sp_ld5
-decode_dir_suffix=rnnlm_1a
-ngram_order=4 # approximate the lattice-rescoring by limiting the max-ngram-order
-              # if it's set, it merges histories in the lattice if they share
-              # the same ngram history and this prevents the lattice from 
-              # exploding exponentially
-pruned_rescore=true
-
-. ./cmd.sh
-. ./utils/parse_options.sh
-
-text=data/train/text
-lexicon=data/local/dict_nosp/lexiconp.txt
-text_dir=data/rnnlm/text_nosp_1e
-mkdir -p $dir/config
-set -e
-
-for f in $text $lexicon; do
-  [ ! -f $f ] && \
-    echo "$0: expected file $f to exist; search for local/wsj_extend_dict.sh in run.sh" && exit 1
-done
-
-if [ $stage -le 0 ]; then
-  mkdir -p $text_dir
-  echo -n >$text_dir/dev.txt
-  # hold out one in every 50 lines as dev data.
-  cat $text | cut -d ' ' -f2- | awk -v text_dir=$text_dir '{if(NR%50 == 0) { print >text_dir"/dev.txt"; } else {print;}}' >$text_dir/train.txt
-fi
-
-if [ $stage -le 1 ]; then
-  cp data/lang/words.txt $dir/config/
-  n=`cat $dir/config/words.txt | wc -l`
-  echo "<brk> $n" >> $dir/config/words.txt
-
-  # words that are not present in words.txt but are in the training or dev data, will be
-  # mapped to <SPOKEN_NOISE> during training.
-  echo "<unk>" >$dir/config/oov.txt
-
-  cat > $dir/config/data_weights.txt <<EOF
-train   10   1.0
-EOF
-
-  rnnlm/get_unigram_probs.py --vocab-file=$dir/config/words.txt \
-                             --unk-word="<unk>" \
-                             --data-weights-file=$dir/config/data_weights.txt \
-                             $text_dir | awk 'NF==2' >$dir/config/unigram_probs.txt
-
-  # choose features
-  rnnlm/choose_features.py --unigram-probs=$dir/config/unigram_probs.txt \
-                           --use-constant-feature=true \
-                           --special-words='<s>,</s>,<brk>,<unk>,<noise>,<spnoise>,<sil>' \
-                           $dir/config/words.txt > $dir/config/features.txt
-
-  cat >$dir/config/xconfig <<EOF
-input dim=$embedding_dim name=input
-relu-renorm-layer name=tdnn1 dim=$embedding_dim input=Append(0, IfDefined(-1))
-fast-lstmp-layer name=lstm1 cell-dim=$embedding_dim recurrent-projection-dim=$lstm_rpd non-recurrent-projection-dim=$lstm_nrpd
-relu-renorm-layer name=tdnn2 dim=$embedding_dim input=Append(0, IfDefined(-2))
-fast-lstmp-layer name=lstm2 cell-dim=$embedding_dim recurrent-projection-dim=$lstm_rpd non-recurrent-projection-dim=$lstm_nrpd
-relu-renorm-layer name=tdnn3 dim=$embedding_dim input=Append(0, IfDefined(-1))
-output-layer name=output include-log-softmax=false dim=$embedding_dim
-EOF
-  rnnlm/validate_config_dir.sh $text_dir $dir/config
-fi
-
-if [ $stage -le 2 ]; then
-  rnnlm/prepare_rnnlm_dir.sh $text_dir $dir/config $dir
-fi
-
-if [ $stage -le 3 ]; then
-  rnnlm/train_rnnlm.sh --num-jobs-initial 1 --num-jobs-final 1 \
-                  --stage $train_stage --num-epochs 10 --cmd "$train_cmd" $dir
-fi
-
-LM=test
-if [ $stage -le 4 ] && $run_rescore; then
-  echo "$0: Perform lattice-rescoring on $ac_model_dir"
-  pruned=
-  if $pruned_rescore; then
-    pruned=_pruned
-  fi
-  for decode_set in dev; do
-    decode_dir=${ac_model_dir}/decode_${decode_set}
-
-    # Lattice rescoring
-    rnnlm/lmrescore$pruned.sh \
-      --cmd "$decode_cmd --mem 4G" \
-      --weight 0.5 --max-ngram-order $ngram_order \
-      data/lang_$LM $dir \
-      data/${decode_set}_hires ${decode_dir} \
-      ${decode_dir}_${decode_dir_suffix}
-  done
-fi
-
-exit 0