diff --git a/egs/aishell/ASR/local/compute_whisper_fbank_aishell.py b/egs/aishell/ASR/local/compute_whisper_fbank_aishell.py
index f1d8a7460..72f4b7acb 100644
--- a/egs/aishell/ASR/local/compute_whisper_fbank_aishell.py
+++ b/egs/aishell/ASR/local/compute_whisper_fbank_aishell.py
@@ -49,8 +49,8 @@ def compute_fbank_aishell(num_mel_bins: int = 80, perturb_speed: bool = False):
 
     dataset_parts = (
         "train",
-        #"dev",
-        #"test",
+        "dev",
+        "test",
     )
     prefix = "aishell"
     suffix = "jsonl.gz"
@@ -69,7 +69,7 @@ def compute_fbank_aishell(num_mel_bins: int = 80, perturb_speed: bool = False):
         dataset_parts,
     )
 
-    extractor = WhisperFbank(WhisperFbankConfig(device='cuda'))
+    extractor = WhisperFbank(WhisperFbankConfig(num_filters=num_mel_bins, device='cuda'))
 
     with get_executor() as ex:  # Initialize the executor only once.
         for partition, m in manifests.items():
diff --git a/egs/aishell/ASR/prepare.sh b/egs/aishell/ASR/prepare.sh
index 78c635690..97dc721c2 100755
--- a/egs/aishell/ASR/prepare.sh
+++ b/egs/aishell/ASR/prepare.sh
@@ -83,9 +83,9 @@ if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
   #
   #   ln -sfv /path/to/musan $dl_dir/musan
   #
-  if [ ! -d $dl_dir/musan ]; then
-    lhotse download musan $dl_dir
-  fi
+  # if [ ! -d $dl_dir/musan ]; then
+  #   lhotse download musan $dl_dir
+  # fi
 fi
 
 if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
@@ -99,17 +99,17 @@ if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
   fi
 fi
 
-if [ $stage -le 2 ] && [ $stop_stage -ge 2 ]; then
-  log "Stage 2: Prepare musan manifest"
-  # We assume that you have downloaded the musan corpus
-  # to data/musan
-  if [ ! -f data/manifests/.musan_manifests.done ]; then
-    log "It may take 6 minutes"
-    mkdir -p data/manifests
-    lhotse prepare musan $dl_dir/musan data/manifests
-    touch data/manifests/.musan_manifests.done
-  fi
-fi
+# if [ $stage -le 2 ] && [ $stop_stage -ge 2 ]; then
+#   log "Stage 2: Prepare musan manifest"
+#   # We assume that you have downloaded the musan corpus
+#   # to data/musan
+#   if [ ! -f data/manifests/.musan_manifests.done ]; then
+#     log "It may take 6 minutes"
+#     mkdir -p data/manifests
+#     lhotse prepare musan $dl_dir/musan data/manifests
+#     touch data/manifests/.musan_manifests.done
+#   fi
+# fi
 
 if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
   log "Stage 3: Compute fbank for aishell"
@@ -120,47 +120,56 @@ if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
   fi
 fi
 
-if [ $stage -le 30 ] && [ $stop_stage -ge 30 ]; then
+# if [ $stage -le 30 ] && [ $stop_stage -ge 30 ]; then
+#   log "Stage 30: Compute whisper fbank for aishell"
+#   if [ ! -f data/fbank/.aishell.done ]; then
+#     mkdir -p data/fbank
+#     ./local/compute_whisper_fbank_aishell.py --perturb-speed True
+#     touch data/fbank/.aishell.done
+#   fi
+# fi
+
+if [ $stage -le 300 ] && [ $stop_stage -ge 300 ]; then
   log "Stage 30: Compute whisper fbank for aishell"
   if [ ! -f data/fbank/.aishell.done ]; then
     mkdir -p data/fbank
-    ./local/compute_whisper_fbank_aishell.py --perturb-speed True
+    ./local/compute_whisper_fbank_aishell.py --perturb-speed True --num-mel-bins 128
     touch data/fbank/.aishell.done
   fi
 fi
 
-if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
-  log "Stage 4: Compute fbank for musan"
-  if [ ! -f data/fbank/.msuan.done ]; then
-    mkdir -p data/fbank
-    ./local/compute_fbank_musan.py
-    touch data/fbank/.msuan.done
-  fi
-fi
+# if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
+#   log "Stage 4: Compute fbank for musan"
+#   if [ ! -f data/fbank/.msuan.done ]; then
+#     mkdir -p data/fbank
+#     ./local/compute_fbank_musan.py
+#     touch data/fbank/.msuan.done
+#   fi
+# fi
 
-if [ $stage -le 40 ] && [ $stop_stage -ge 40 ]; then
-  log "Stage 4: Compute fbank for musan"
-  if [ ! -f data/fbank/.msuan.done ]; then
-    mkdir -p data/fbank
-    ./local/compute_whisper_fbank_musan.py
-    touch data/fbank/.msuan.done
-  fi
-fi
+# if [ $stage -le 40 ] && [ $stop_stage -ge 40 ]; then
+#   log "Stage 4: Compute fbank for musan"
+#   if [ ! -f data/fbank/.msuan.done ]; then
+#     mkdir -p data/fbank
+#     ./local/compute_whisper_fbank_musan.py
+#     touch data/fbank/.msuan.done
+#   fi
+# fi
 
-lang_phone_dir=data/lang_phone
-if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
-  log "Stage 5: Prepare phone based lang"
-  mkdir -p $lang_phone_dir
+# lang_phone_dir=data/lang_phone
+# if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
+#   log "Stage 5: Prepare phone based lang"
+#   mkdir -p $lang_phone_dir
 
-  (echo '!SIL SIL'; echo '<SPOKEN_NOISE> SPN'; echo '<UNK> SPN'; ) |
-    cat - $dl_dir/aishell/resource_aishell/lexicon.txt |
-    sort | uniq > $lang_phone_dir/lexicon.txt
+#   (echo '!SIL SIL'; echo '<SPOKEN_NOISE> SPN'; echo '<UNK> SPN'; ) |
+#     cat - $dl_dir/aishell/resource_aishell/lexicon.txt |
+#     sort | uniq > $lang_phone_dir/lexicon.txt
 
-  ./local/generate_unique_lexicon.py --lang-dir $lang_phone_dir
+#   ./local/generate_unique_lexicon.py --lang-dir $lang_phone_dir
 
-  if [ ! -f $lang_phone_dir/L_disambig.pt ]; then
-    ./local/prepare_lang.py --lang-dir $lang_phone_dir
-  fi
+#   if [ ! -f $lang_phone_dir/L_disambig.pt ]; then
+#     ./local/prepare_lang.py --lang-dir $lang_phone_dir
+#   fi
 
 
   # Train a bigram P for MMI training
@@ -173,93 +182,93 @@ if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
 	    cut -d " " -f 2- > $lang_phone_dir/transcript_words.txt
   fi
 
-  if [ ! -f $lang_phone_dir/transcript_tokens.txt ]; then
-    ./local/convert_transcript_words_to_tokens.py \
-      --lexicon $lang_phone_dir/uniq_lexicon.txt \
-      --transcript $lang_phone_dir/transcript_words.txt \
-      --oov "<UNK>" \
-      > $lang_phone_dir/transcript_tokens.txt
-  fi
+#   if [ ! -f $lang_phone_dir/transcript_tokens.txt ]; then
+#     ./local/convert_transcript_words_to_tokens.py \
+#       --lexicon $lang_phone_dir/uniq_lexicon.txt \
+#       --transcript $lang_phone_dir/transcript_words.txt \
+#       --oov "<UNK>" \
+#       > $lang_phone_dir/transcript_tokens.txt
+#   fi
 
-  if [ ! -f $lang_phone_dir/P.arpa ]; then
-    ./shared/make_kn_lm.py \
-      -ngram-order 2 \
-      -text $lang_phone_dir/transcript_tokens.txt \
-      -lm $lang_phone_dir/P.arpa
-  fi
+#   if [ ! -f $lang_phone_dir/P.arpa ]; then
+#     ./shared/make_kn_lm.py \
+#       -ngram-order 2 \
+#       -text $lang_phone_dir/transcript_tokens.txt \
+#       -lm $lang_phone_dir/P.arpa
+#   fi
 
-  if [ ! -f $lang_phone_dir/P.fst.txt ]; then
-    python3 -m kaldilm \
-      --read-symbol-table="$lang_phone_dir/tokens.txt" \
-      --disambig-symbol='#0' \
-      --max-order=2 \
-      $lang_phone_dir/P.arpa > $lang_phone_dir/P.fst.txt
-  fi
-fi
+#   if [ ! -f $lang_phone_dir/P.fst.txt ]; then
+#     python3 -m kaldilm \
+#       --read-symbol-table="$lang_phone_dir/tokens.txt" \
+#       --disambig-symbol='#0' \
+#       --max-order=2 \
+#       $lang_phone_dir/P.arpa > $lang_phone_dir/P.fst.txt
+#   fi
+# fi
 
-lang_char_dir=data/lang_char
-if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
-  log "Stage 6: Prepare char based lang"
-  mkdir -p $lang_char_dir
-  # We reuse words.txt from phone based lexicon
-  # so that the two can share G.pt later.
+# lang_char_dir=data/lang_char
+# if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
+#   log "Stage 6: Prepare char based lang"
+#   mkdir -p $lang_char_dir
+#   # We reuse words.txt from phone based lexicon
+#   # so that the two can share G.pt later.
 
-  # The transcripts in training set, generated in stage 5
-  cp $lang_phone_dir/transcript_words.txt $lang_char_dir/transcript_words.txt
+#   # The transcripts in training set, generated in stage 5
+#   cp $lang_phone_dir/transcript_words.txt $lang_char_dir/transcript_words.txt
 
-  cat $dl_dir/aishell/data_aishell/transcript/aishell_transcript_v0.8.txt |
-  cut -d " " -f 2- > $lang_char_dir/text
+#   cat $dl_dir/aishell/data_aishell/transcript/aishell_transcript_v0.8.txt |
+#   cut -d " " -f 2- > $lang_char_dir/text
 
-  (echo '<eps> 0'; echo '!SIL 1'; echo '<SPOKEN_NOISE> 2'; echo '<UNK> 3';) \
-    > $lang_char_dir/words.txt
+#   (echo '<eps> 0'; echo '!SIL 1'; echo '<SPOKEN_NOISE> 2'; echo '<UNK> 3';) \
+#     > $lang_char_dir/words.txt
 
-  cat $lang_char_dir/text | sed 's/ /\n/g' | sort -u | sed '/^$/d' \
-     | awk '{print $1" "NR+3}' >> $lang_char_dir/words.txt
+#   cat $lang_char_dir/text | sed 's/ /\n/g' | sort -u | sed '/^$/d' \
+#      | awk '{print $1" "NR+3}' >> $lang_char_dir/words.txt
 
-  num_lines=$(< $lang_char_dir/words.txt wc -l)
-  (echo "#0 $num_lines"; echo "<s> $(($num_lines + 1))"; echo "</s> $(($num_lines + 2))";) \
-    >> $lang_char_dir/words.txt
+#   num_lines=$(< $lang_char_dir/words.txt wc -l)
+#   (echo "#0 $num_lines"; echo "<s> $(($num_lines + 1))"; echo "</s> $(($num_lines + 2))";) \
+#     >> $lang_char_dir/words.txt
 
-  if [ ! -f $lang_char_dir/L_disambig.pt ]; then
-    ./local/prepare_char.py --lang-dir $lang_char_dir
-  fi
-fi
+#   if [ ! -f $lang_char_dir/L_disambig.pt ]; then
+#     ./local/prepare_char.py --lang-dir $lang_char_dir
+#   fi
+# fi
 
-if [ $stage -le 7 ] && [ $stop_stage -ge 7 ]; then
-  log "Stage 7: Prepare Byte BPE based lang"
+# if [ $stage -le 7 ] && [ $stop_stage -ge 7 ]; then
+#   log "Stage 7: Prepare Byte BPE based lang"
 
-  for vocab_size in ${vocab_sizes[@]}; do
-    lang_dir=data/lang_bbpe_${vocab_size}
-    mkdir -p $lang_dir
+#   for vocab_size in ${vocab_sizes[@]}; do
+#     lang_dir=data/lang_bbpe_${vocab_size}
+#     mkdir -p $lang_dir
 
-    cp $lang_char_dir/words.txt $lang_dir
-    cp $lang_char_dir/text $lang_dir
+#     cp $lang_char_dir/words.txt $lang_dir
+#     cp $lang_char_dir/text $lang_dir
 
-    if [ ! -f $lang_dir/bbpe.model ]; then
-      ./local/train_bbpe_model.py \
-        --lang-dir $lang_dir \
-        --vocab-size $vocab_size \
-        --transcript $lang_dir/text
-    fi
+#     if [ ! -f $lang_dir/bbpe.model ]; then
+#       ./local/train_bbpe_model.py \
+#         --lang-dir $lang_dir \
+#         --vocab-size $vocab_size \
+#         --transcript $lang_dir/text
+#     fi
 
-    if [ ! -f $lang_dir/L_disambig.pt ]; then
-      ./local/prepare_lang_bbpe.py --lang-dir $lang_dir
-    fi
-  done
-fi
+#     if [ ! -f $lang_dir/L_disambig.pt ]; then
+#       ./local/prepare_lang_bbpe.py --lang-dir $lang_dir
+#     fi
+#   done
+# fi
 
-if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
-  log "Stage 8: Prepare G"
+# if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
+#   log "Stage 8: Prepare G"
 
-  mkdir -p data/lm
+#   mkdir -p data/lm
 
-  # Train LM on transcripts
-  if [ ! -f data/lm/3-gram.unpruned.arpa ]; then
-    python3 ./shared/make_kn_lm.py \
-      -ngram-order 3 \
-      -text $lang_char_dir/transcript_words.txt \
-      -lm data/lm/3-gram.unpruned.arpa
-  fi
+#   # Train LM on transcripts
+#   if [ ! -f data/lm/3-gram.unpruned.arpa ]; then
+#     python3 ./shared/make_kn_lm.py \
+#       -ngram-order 3 \
+#       -text $lang_char_dir/transcript_words.txt \
+#       -lm data/lm/3-gram.unpruned.arpa
+#   fi
 
   # We assume you have installed kaldilm, if not, please install
   # it using: pip install kaldilm
@@ -285,112 +294,112 @@ if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
   fi
 fi
 
-if [ $stage -le 9 ] && [ $stop_stage -ge 9 ]; then
-  log "Stage 9: Compile LG & HLG"
-  ./local/compile_hlg.py --lang-dir $lang_phone_dir --lm G_3_gram_phone
-  ./local/compile_hlg.py --lang-dir $lang_char_dir --lm G_3_gram_char
-  for vocab_size in ${vocab_sizes[@]}; do
-    lang_dir=data/lang_bbpe_${vocab_size}
-    ./local/compile_hlg.py --lang-dir $lang_dir --lm G_3_gram_char
-  done
+# if [ $stage -le 9 ] && [ $stop_stage -ge 9 ]; then
+#   log "Stage 9: Compile LG & HLG"
+#   ./local/compile_hlg.py --lang-dir $lang_phone_dir --lm G_3_gram_phone
+#   ./local/compile_hlg.py --lang-dir $lang_char_dir --lm G_3_gram_char
+#   for vocab_size in ${vocab_sizes[@]}; do
+#     lang_dir=data/lang_bbpe_${vocab_size}
+#     ./local/compile_hlg.py --lang-dir $lang_dir --lm G_3_gram_char
+#   done
 
-  ./local/compile_lg.py --lang-dir $lang_phone_dir --lm G_3_gram_phone
-  ./local/compile_lg.py --lang-dir $lang_char_dir --lm G_3_gram_char
-  for vocab_size in ${vocab_sizes[@]}; do
-    lang_dir=data/lang_bbpe_${vocab_size}
-    ./local/compile_lg.py --lang-dir $lang_dir --lm G_3_gram_char
-  done
-fi
+#   ./local/compile_lg.py --lang-dir $lang_phone_dir --lm G_3_gram_phone
+#   ./local/compile_lg.py --lang-dir $lang_char_dir --lm G_3_gram_char
+#   for vocab_size in ${vocab_sizes[@]}; do
+#     lang_dir=data/lang_bbpe_${vocab_size}
+#     ./local/compile_lg.py --lang-dir $lang_dir --lm G_3_gram_char
+#   done
+# fi
 
-if [ $stage -le 10 ] && [ $stop_stage -ge 10 ]; then
-  log "Stage 10: Generate LM training data"
+# if [ $stage -le 10 ] && [ $stop_stage -ge 10 ]; then
+#   log "Stage 10: Generate LM training data"
 
-  log "Processing char based data"
-  out_dir=data/lm_training_char
-  mkdir -p $out_dir $dl_dir/lm
+#   log "Processing char based data"
+#   out_dir=data/lm_training_char
+#   mkdir -p $out_dir $dl_dir/lm
 
-  if [ ! -f $dl_dir/lm/aishell-train-word.txt ]; then
-    cp $lang_phone_dir/transcript_words.txt $dl_dir/lm/aishell-train-word.txt
-  fi
+#   if [ ! -f $dl_dir/lm/aishell-train-word.txt ]; then
+#     cp $lang_phone_dir/transcript_words.txt $dl_dir/lm/aishell-train-word.txt
+#   fi
 
-  # training words
-  ./local/prepare_char_lm_training_data.py \
-    --lang-char data/lang_char \
-    --lm-data $dl_dir/lm/aishell-train-word.txt \
-    --lm-archive $out_dir/lm_data.pt
+#   # training words
+#   ./local/prepare_char_lm_training_data.py \
+#     --lang-char data/lang_char \
+#     --lm-data $dl_dir/lm/aishell-train-word.txt \
+#     --lm-archive $out_dir/lm_data.pt
 
-  # valid words
-  if [ ! -f $dl_dir/lm/aishell-valid-word.txt ]; then
-    aishell_text=$dl_dir/aishell/data_aishell/transcript/aishell_transcript_v0.8.txt
-    aishell_valid_uid=$dl_dir/aishell/data_aishell/transcript/aishell_valid_uid
-    find $dl_dir/aishell/data_aishell/wav/dev -name "*.wav" | sed 's/\.wav//g' | awk -F '/' '{print $NF}' > $aishell_valid_uid
-    awk 'NR==FNR{uid[$1]=$1} NR!=FNR{if($1 in uid) print $0}' $aishell_valid_uid $aishell_text |
-	    cut -d " " -f 2- > $dl_dir/lm/aishell-valid-word.txt
-  fi
+#   # valid words
+#   if [ ! -f $dl_dir/lm/aishell-valid-word.txt ]; then
+#     aishell_text=$dl_dir/aishell/data_aishell/transcript/aishell_transcript_v0.8.txt
+#     aishell_valid_uid=$dl_dir/aishell/data_aishell/transcript/aishell_valid_uid
+#     find $dl_dir/aishell/data_aishell/wav/dev -name "*.wav" | sed 's/\.wav//g' | awk -F '/' '{print $NF}' > $aishell_valid_uid
+#     awk 'NR==FNR{uid[$1]=$1} NR!=FNR{if($1 in uid) print $0}' $aishell_valid_uid $aishell_text |
+# 	    cut -d " " -f 2- > $dl_dir/lm/aishell-valid-word.txt
+#   fi
 
-  ./local/prepare_char_lm_training_data.py \
-    --lang-char data/lang_char \
-    --lm-data $dl_dir/lm/aishell-valid-word.txt \
-    --lm-archive $out_dir/lm_data_valid.pt
+#   ./local/prepare_char_lm_training_data.py \
+#     --lang-char data/lang_char \
+#     --lm-data $dl_dir/lm/aishell-valid-word.txt \
+#     --lm-archive $out_dir/lm_data_valid.pt
 
-  # test words
-  if [ ! -f $dl_dir/lm/aishell-test-word.txt ]; then
-    aishell_text=$dl_dir/aishell/data_aishell/transcript/aishell_transcript_v0.8.txt
-    aishell_test_uid=$dl_dir/aishell/data_aishell/transcript/aishell_test_uid
-    find $dl_dir/aishell/data_aishell/wav/test -name "*.wav" | sed 's/\.wav//g' | awk -F '/' '{print $NF}' > $aishell_test_uid
-    awk 'NR==FNR{uid[$1]=$1} NR!=FNR{if($1 in uid) print $0}' $aishell_test_uid $aishell_text |
-	    cut -d " " -f 2- > $dl_dir/lm/aishell-test-word.txt
-  fi
+#   # test words
+#   if [ ! -f $dl_dir/lm/aishell-test-word.txt ]; then
+#     aishell_text=$dl_dir/aishell/data_aishell/transcript/aishell_transcript_v0.8.txt
+#     aishell_test_uid=$dl_dir/aishell/data_aishell/transcript/aishell_test_uid
+#     find $dl_dir/aishell/data_aishell/wav/test -name "*.wav" | sed 's/\.wav//g' | awk -F '/' '{print $NF}' > $aishell_test_uid
+#     awk 'NR==FNR{uid[$1]=$1} NR!=FNR{if($1 in uid) print $0}' $aishell_test_uid $aishell_text |
+# 	    cut -d " " -f 2- > $dl_dir/lm/aishell-test-word.txt
+#   fi
 
-  ./local/prepare_char_lm_training_data.py \
-    --lang-char data/lang_char \
-    --lm-data $dl_dir/lm/aishell-test-word.txt \
-    --lm-archive $out_dir/lm_data_test.pt
-fi
+#   ./local/prepare_char_lm_training_data.py \
+#     --lang-char data/lang_char \
+#     --lm-data $dl_dir/lm/aishell-test-word.txt \
+#     --lm-archive $out_dir/lm_data_test.pt
+# fi
 
 
-if [ $stage -le 11 ] && [ $stop_stage -ge 11 ]; then
-  log "Stage 11: Sort LM training data"
-  # Sort LM training data by sentence length in descending order
-  # for ease of training.
-  #
-  # Sentence length equals to the number of tokens
-  # in a sentence.
+# if [ $stage -le 11 ] && [ $stop_stage -ge 11 ]; then
+#   log "Stage 11: Sort LM training data"
+#   # Sort LM training data by sentence length in descending order
+#   # for ease of training.
+#   #
+#   # Sentence length equals to the number of tokens
+#   # in a sentence.
 
-  out_dir=data/lm_training_char
-  mkdir -p $out_dir
-  ln -snf ../../../librispeech/ASR/local/sort_lm_training_data.py local/
+#   out_dir=data/lm_training_char
+#   mkdir -p $out_dir
+#   ln -snf ../../../librispeech/ASR/local/sort_lm_training_data.py local/
 
-  ./local/sort_lm_training_data.py \
-    --in-lm-data $out_dir/lm_data.pt \
-    --out-lm-data $out_dir/sorted_lm_data.pt \
-    --out-statistics $out_dir/statistics.txt
+#   ./local/sort_lm_training_data.py \
+#     --in-lm-data $out_dir/lm_data.pt \
+#     --out-lm-data $out_dir/sorted_lm_data.pt \
+#     --out-statistics $out_dir/statistics.txt
 
-  ./local/sort_lm_training_data.py \
-    --in-lm-data $out_dir/lm_data_valid.pt \
-    --out-lm-data $out_dir/sorted_lm_data-valid.pt \
-    --out-statistics $out_dir/statistics-valid.txt
+#   ./local/sort_lm_training_data.py \
+#     --in-lm-data $out_dir/lm_data_valid.pt \
+#     --out-lm-data $out_dir/sorted_lm_data-valid.pt \
+#     --out-statistics $out_dir/statistics-valid.txt
 
-  ./local/sort_lm_training_data.py \
-    --in-lm-data $out_dir/lm_data_test.pt \
-    --out-lm-data $out_dir/sorted_lm_data-test.pt \
-    --out-statistics $out_dir/statistics-test.txt
-fi
+#   ./local/sort_lm_training_data.py \
+#     --in-lm-data $out_dir/lm_data_test.pt \
+#     --out-lm-data $out_dir/sorted_lm_data-test.pt \
+#     --out-statistics $out_dir/statistics-test.txt
+# fi
 
-if [ $stage -le 12 ] && [ $stop_stage -ge 12 ]; then
-  log "Stage 11: Train RNN LM model"
-  python ../../../icefall/rnn_lm/train.py \
-    --start-epoch 0 \
-    --world-size 1 \
-    --num-epochs 20 \
-    --use-fp16 0 \
-    --embedding-dim 512 \
-    --hidden-dim 512 \
-    --num-layers 2 \
-    --batch-size 400 \
-    --exp-dir rnnlm_char/exp \
-    --lm-data $out_dir/sorted_lm_data.pt \
-    --lm-data-valid $out_dir/sorted_lm_data-valid.pt \
-    --vocab-size 4336 \
-    --master-port 12345
-fi
+# if [ $stage -le 12 ] && [ $stop_stage -ge 12 ]; then
+#   log "Stage 11: Train RNN LM model"
+#   python ../../../icefall/rnn_lm/train.py \
+#     --start-epoch 0 \
+#     --world-size 1 \
+#     --num-epochs 20 \
+#     --use-fp16 0 \
+#     --embedding-dim 512 \
+#     --hidden-dim 512 \
+#     --num-layers 2 \
+#     --batch-size 400 \
+#     --exp-dir rnnlm_char/exp \
+#     --lm-data $out_dir/sorted_lm_data.pt \
+#     --lm-data-valid $out_dir/sorted_lm_data-valid.pt \
+#     --vocab-size 4336 \
+#     --master-port 12345
+# fi
diff --git a/egs/aishell/ASR/tdnn_lstm_ctc/asr_datamodule.py b/egs/aishell/ASR/tdnn_lstm_ctc/asr_datamodule.py
index 293a1a569..df21a9508 100644
--- a/egs/aishell/ASR/tdnn_lstm_ctc/asr_datamodule.py
+++ b/egs/aishell/ASR/tdnn_lstm_ctc/asr_datamodule.py
@@ -176,7 +176,7 @@ class AishellAsrDataModule:
         group.add_argument(
             "--enable-musan",
             type=str2bool,
-            default=True,
+            default=False,
             help="When enabled, select noise from MUSAN and mix it"
             "with training dataset. ",
         )
@@ -192,11 +192,11 @@ class AishellAsrDataModule:
             The state dict for the training sampler.
         """
         logging.info("About to get Musan cuts")
-        cuts_musan = load_manifest(self.args.manifest_dir / "musan_cuts.jsonl.gz")
 
         transforms = []
         if self.args.enable_musan:
             logging.info("Enable MUSAN")
+            cuts_musan = load_manifest(self.args.manifest_dir / "musan_cuts.jsonl.gz")
             transforms.append(
                 CutMix(cuts=cuts_musan, p=0.5, snr=(10, 20), preserve_id=True)
             )
diff --git a/egs/aishell/ASR/whisper/decode.py b/egs/aishell/ASR/whisper/decode.py
index 578546bbe..2d8dbbfc3 100644
--- a/egs/aishell/ASR/whisper/decode.py
+++ b/egs/aishell/ASR/whisper/decode.py
@@ -127,6 +127,15 @@ def get_parser():
         help="The experiment dir",
     )
 
+    parser.add_argument(
+        "--model-name",
+        type=str,
+        default="large-v2",
+        choices=["large-v2", "large-v3", "medium", "small", "tiny"],
+        help="""The model name to use.
+        """,
+    )
+  
     return parser
 
 
@@ -370,7 +379,7 @@ def main():
 
     logging.info(f"device: {device}")
 
-    model = whisper.load_model("medium")
+    model = whisper.load_model(params.model_name)
     if params.epoch > 0:
       if params.avg > 1:
         start = params.epoch - params.avg
diff --git a/egs/aishell/ASR/whisper/ds_config_zero1.json b/egs/aishell/ASR/whisper/ds_config_zero1.json
index 59318968e..0d69f83b9 100644
--- a/egs/aishell/ASR/whisper/ds_config_zero1.json
+++ b/egs/aishell/ASR/whisper/ds_config_zero1.json
@@ -2,10 +2,10 @@
     "fp16": {
         "enabled": true,
         "loss_scale": 0,
-        "loss_scale_window": 1000,
+        "loss_scale_window": 100,
         "initial_scale_power": 16,
         "hysteresis": 2,
-        "min_loss_scale": 1
+        "min_loss_scale": 0.01
     },
     "zero_optimization": {
         "stage": 1,
@@ -19,8 +19,8 @@
     "scheduler": {
         "type": "WarmupLR",
         "params": {
-            "warmup_min_lr": 5e-6,
-            "warmup_max_lr": 1e-5,
+            "warmup_min_lr": 1e-6,
+            "warmup_max_lr": 5e-6,
             "warmup_num_steps": 100
         }
     },
diff --git a/egs/aishell/ASR/whisper/model.py b/egs/aishell/ASR/whisper/model.py
index 89d76383a..4e0ef28fa 100644
--- a/egs/aishell/ASR/whisper/model.py
+++ b/egs/aishell/ASR/whisper/model.py
@@ -2,6 +2,8 @@ import torch
 import torch.nn as nn
 import base64
 import gzip
+import warnings
+from tqdm import tqdm
 from dataclasses import dataclass
 from typing import Dict, Iterable, Optional, Union
 import os
@@ -275,6 +277,11 @@ class Whisper(nn.Module):
     @property
     def is_multilingual(self):
         return self.dims.n_vocab == 51865
+        return self.dims.n_vocab >= 51865
+
+    @property
+    def num_languages(self):
+        return self.dims.n_vocab - 51765 - int(self.is_multilingual)
 
     def install_kv_cache_hooks(self, cache: Optional[dict] = None):
         """
@@ -324,6 +331,7 @@ _MODELS = {
     "medium": "https://openaipublic.azureedge.net/main/whisper/models/345ae4da62f9b3d59415adc60127b97c714f32e89e936602e85993674d08dcb1/medium.pt",
     "large-v1": "https://openaipublic.azureedge.net/main/whisper/models/e4b87e7e0bf463eb8e6956e646f1e277e901512310def2c24bf0e11bd3c28e9a/large-v1.pt",
     "large-v2": "https://openaipublic.azureedge.net/main/whisper/models/81f7c96c852ee8fc832187b0132e569d6c3065a3252ed18e56effd0b6a73e524/large-v2.pt",
+    "large-v3": "https://openaipublic.azureedge.net/main/whisper/models/e5b1a55b89c1367dacf97e3e19bfd829a01529dbfdeefa8caeb59b3f1b81dadb/large-v3.pt",
     "large": "https://openaipublic.azureedge.net/main/whisper/models/81f7c96c852ee8fc832187b0132e569d6c3065a3252ed18e56effd0b6a73e524/large-v2.pt",
 }
 
diff --git a/egs/aishell/ASR/whisper/requirements.txt b/egs/aishell/ASR/whisper/requirements.txt
index b71e4a4ad..52bcf1196 100644
--- a/egs/aishell/ASR/whisper/requirements.txt
+++ b/egs/aishell/ASR/whisper/requirements.txt
@@ -1,11 +1,11 @@
 k2
 kaldialign
-lhotse==1.18
-#git+https://github.com/lhotse-speech/lhotse
+#lhotse==1.18
+git+https://github.com/lhotse-speech/lhotse
 sentencepiece
 tensorboard
 librosa
-openai-whisper
+openai-whisper==20231117
 zhconv
 WeTextProcessing
 deepspeed
diff --git a/egs/aishell/ASR/whisper/train.py b/egs/aishell/ASR/whisper/train.py
index 158ad9443..d2937c9ee 100644
--- a/egs/aishell/ASR/whisper/train.py
+++ b/egs/aishell/ASR/whisper/train.py
@@ -796,7 +796,7 @@ def run(rank, world_size, args):
     logging.info(f"Number of model parameters: {num_param}")
 
     tokenizer = whisper.tokenizer.get_tokenizer(
-        model.is_multilingual, language="zh", task="transcribe"
+        model.is_multilingual, num_languages=model.num_languages, language="zh", task="transcribe"
     )
 
     assert params.save_every_n >= params.average_period