from local

egs/tedlium2/ASR/prepare.sh

@@ -172,68 +172,42 @@ if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
 fi
 
 if [ $stage -le 7 ] && [ $stop_stage -ge 7 ]; then
-  log "Stage 7: Prepare bigram P"
-
-  for vocab_size in ${vocab_sizes[@]}; do
-    lang_dir=data/lang_bpe_${vocab_size}
-
-    if [ ! -f $lang_dir/transcript_tokens.txt ]; then
-      ./local/convert_transcript_words_to_tokens.py \
-        --lexicon $lang_dir/lexicon.txt \
-        --transcript $lang_dir/transcript_words.txt \
-        --oov "<UNK>" \
-        > $lang_dir/transcript_tokens.txt
-    fi
-
-    if [ ! -f $lang_dir/P.arpa ]; then
-      ./shared/make_kn_lm.py \
-        -ngram-order 2 \
-        -text $lang_dir/transcript_tokens.txt \
-        -lm $lang_dir/P.arpa
-    fi
-
-    if [ ! -f $lang_dir/P.fst.txt ]; then
-      python3 -m kaldilm \
-        --read-symbol-table="$lang_dir/tokens.txt" \
-        --disambig-symbol='#0' \
-        --max-order=2 \
-        $lang_dir/P.arpa > $lang_dir/P.fst.txt
-    fi
-  done
-fi
-
-if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
-  log "Stage 8: Prepare G"
+  log "Stage 7: Prepare G"
   # We assume you have install kaldilm, if not, please install
   # it using: pip install kaldilm
 
   mkdir -p data/lm
-  if [ ! -f data/lm/G_3_gram.fst.txt ]; then
+  if [ ! -f data/lm/G_4_gram_small.fst.txt ]; then
     # It is used in building HLG
     python3 -m kaldilm \
-      --read-symbol-table="data/lang_phone/words.txt" \
-      --disambig-symbol='#0' \
-      --max-order=3 \
-      $dl_dir/lm/3-gram.pruned.1e-7.arpa > data/lm/G_3_gram.fst.txt
-  fi
-
-  if [ ! -f data/lm/G_4_gram.fst.txt ]; then
-    # It is used for LM rescoring
-    python3 -m kaldilm \
-      --read-symbol-table="data/lang_phone/words.txt" \
+      --read-symbol-table="data/lang/words.txt" \
       --disambig-symbol='#0' \
       --max-order=4 \
-      $dl_dir/lm/4-gram.arpa > data/lm/G_4_gram.fst.txt
+      --max-arpa-warnings=-1 \
+      $dl_dir/lm/4gram_small.arpa > data/lm/G_4_gram_small.fst.txt
+  fi
+
+  if [ ! -f data/lm/G_4_gram_big.fst.txt ]; then
+    # It is used for LM rescoring
+    python3 -m kaldilm \
+      --read-symbol-table="data/lang/words.txt" \
+      --disambig-symbol='#0' \
+      --max-order=4 \
+      --max-arpa-warnings=-1 \
+      $dl_dir/lm/4gram_big.arpa > data/lm/G_4_gram_big.fst.txt
   fi
 fi
 
-if [ $stage -le 9 ] && [ $stop_stage -ge 9 ]; then
-  log "Stage 9: Compile HLG"
-  ./local/compile_hlg.py --lang-dir data/lang_phone
+if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
+  log "Stage 8: Compile HLG"
 
   for vocab_size in ${vocab_sizes[@]}; do
     lang_dir=data/lang_bpe_${vocab_size}
-    ./local/compile_hlg.py --lang-dir $lang_dir
+
+    if [ ! -f $lang_dir/HLG.pt ]; then
+      ./local/compile_hlg.py \
+        --lang-dir $lang_dir \
+        --lm G_4_gram_small
+    fi
   done
 fi
-