vocab into data/lang_char

examples/aishell/asr0/conf/deepspeech2.yaml

@@ -14,7 +14,7 @@ collator:
   batch_size: 64 # one gpu
   mean_std_filepath: data/mean_std.json
   unit_type: char
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   augmentation_config: conf/augmentation.json
   random_seed: 0
   spm_model_prefix: 

examples/aishell/asr0/conf/deepspeech2_online.yaml

@@ -14,7 +14,7 @@ collator:
   batch_size: 64 # one gpu
   mean_std_filepath: data/mean_std.json
   unit_type: char
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   augmentation_config: conf/augmentation.json
   random_seed: 0
   spm_model_prefix: 

examples/aishell/asr0/local/data.sh

@@ -3,9 +3,12 @@
 stage=-1
 stop_stage=100
 
-source ${MAIN_ROOT}/utils/parse_options.sh
+dict_dir=data/lang_char
+
+. ${MAIN_ROOT}/utils/parse_options.sh || exit -1;
 
 mkdir -p data
+mkdir -p ${dict_dir}
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 
@@ -52,7 +55,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     python3 ${MAIN_ROOT}/utils/build_vocab.py \
     --unit_type="char" \
     --count_threshold=0 \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths "data/manifest.train.raw" "data/manifest.dev.raw"
 
     if [ $? -ne 0 ]; then
@@ -68,7 +71,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         python3 ${MAIN_ROOT}/utils/format_data.py \
                 --cmvn_path "data/mean_std.json" \
                 --unit_type "char" \
-                --vocab_path="data/vocab.txt" \
+                --vocab_path="${dict_dir}/vocab.txt" \
                 --manifest_path="data/manifest.${dataset}.raw" \
                 --output_path="data/manifest.${dataset}"
 

examples/aishell/asr1/conf/chunk_conformer.yaml

@@ -12,7 +12,7 @@ data:
   
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'char'
   spm_model_prefix: ''
   augmentation_config: conf/preprocess.yaml

examples/aishell/asr1/conf/conformer.yaml

@@ -12,7 +12,7 @@ data:
 
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'char'
   spm_model_prefix: ''
   augmentation_config: conf/preprocess.yaml

examples/aishell/asr1/conf/transformer.yaml

@@ -12,7 +12,7 @@ data:
 
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'char'
   spm_model_prefix: ''
   augmentation_config: conf/preprocess.yaml

examples/aishell/asr1/local/data.sh

@@ -2,10 +2,12 @@
 
 stage=-1
 stop_stage=100
+dict_dir=data/lang_char
 
-source ${MAIN_ROOT}/utils/parse_options.sh
+. ${MAIN_ROOT}/utils/parse_options.sh || exit -1;
 
 mkdir -p data
+mkdir -p ${dict_dir}
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 
@@ -53,7 +55,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     python3 ${MAIN_ROOT}/utils/build_vocab.py \
     --unit_type="char" \
     --count_threshold=0 \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths "data/manifest.train.raw"
 
     if [ $? -ne 0 ]; then
@@ -69,7 +71,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         python3 ${MAIN_ROOT}/utils/format_data.py \
             --cmvn_path "data/mean_std.json" \
             --unit_type "char" \
-            --vocab_path="data/vocab.txt" \
+            --vocab_path="${dict_dir}/vocab.txt" \
             --manifest_path="data/manifest.${dataset}.raw" \
             --output_path="data/manifest.${dataset}"
 

examples/callcenter/asr1/conf/chunk_conformer.yaml

@@ -12,7 +12,7 @@ data:
   
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'char'
   spm_model_prefix: ''
   augmentation_config: conf/preprocess.yaml

examples/callcenter/asr1/conf/conformer.yaml

@@ -12,7 +12,7 @@ data:
 
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'char'
   spm_model_prefix: ''
   augmentation_config: conf/preprocess.yaml

examples/callcenter/asr1/local/data.sh

@@ -2,10 +2,12 @@
 
 stage=-1
 stop_stage=100
+dict_dir=data/lang_char
 
 source ${MAIN_ROOT}/utils/parse_options.sh
 
 mkdir -p data
+mkdir -p ${dict_dir}
 
 if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
     for dataset in train dev test; do
@@ -41,7 +43,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     python3 ${MAIN_ROOT}/utils/build_vocab.py \
     --unit_type="char" \
     --count_threshold=0 \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths "data/manifest.train.raw"
 
     if [ $? -ne 0 ]; then
@@ -57,7 +59,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         python3 ${MAIN_ROOT}/utils/format_data.py \
             --cmvn_path "data/mean_std.json" \
             --unit_type "char" \
-            --vocab_path="data/vocab.txt" \
+            --vocab_path="${dict_dir}/vocab.txt" \
             --manifest_path="data/manifest.${dataset}.raw" \
             --output_path="data/manifest.${dataset}"
 

examples/librispeech/asr0/conf/deepspeech2.yaml

@@ -14,7 +14,7 @@ collator:
   batch_size: 20
   mean_std_filepath: data/mean_std.json
   unit_type: char
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt
   augmentation_config: conf/augmentation.json
   random_seed: 0
   spm_model_prefix: 

examples/librispeech/asr0/conf/deepspeech2_online.yaml

@@ -14,7 +14,7 @@ collator:
   batch_size: 15
   mean_std_filepath: data/mean_std.json
   unit_type: char
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt
   augmentation_config: conf/augmentation.json
   random_seed: 0
   spm_model_prefix: 

examples/librispeech/asr0/local/data.sh

@@ -4,10 +4,12 @@ stage=-1
 stop_stage=100
 
 unit_type=char
+dict_dir=data/lang_char
 
 source ${MAIN_ROOT}/utils/parse_options.sh
 
 mkdir -p data
+mkdir -p ${dict_dir}
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 
@@ -67,7 +69,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     python3 ${MAIN_ROOT}/utils/build_vocab.py \
     --unit_type ${unit_type} \
     --count_threshold=0 \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths="data/manifest.train.raw"
 
     if [ $? -ne 0 ]; then
@@ -83,7 +85,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         python3 ${MAIN_ROOT}/utils/format_data.py \
         --cmvn_path "data/mean_std.json" \
         --unit_type ${unit_type} \
-        --vocab_path="data/vocab.txt" \
+        --vocab_path="${dict_dir}/vocab.txt" \
         --manifest_path="data/manifest.${set}.raw" \
         --output_path="data/manifest.${set}"
 

examples/librispeech/asr1/conf/chunk_conformer.yaml

@@ -11,9 +11,9 @@ data:
   max_output_input_ratio: 100.0
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'spm'
-  spm_model_prefix: 'data/bpe_unigram_5000'
+  spm_model_prefix: 'data/lang_char/bpe_unigram_5000'
   mean_std_filepath: ""
   augmentation_config: conf/preprocess.yaml
   batch_size: 16

examples/librispeech/asr1/conf/conformer.yaml

@@ -11,9 +11,9 @@ data:
   max_output_input_ratio: 100.0
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'spm'
-  spm_model_prefix: 'data/bpe_unigram_5000'
+  spm_model_prefix: 'data/lang_char/bpe_unigram_5000'
   mean_std_filepath: ""
   augmentation_config: conf/preprocess.yaml
   batch_size: 16

examples/librispeech/asr1/conf/transformer.yaml

@@ -11,9 +11,9 @@ data:
   max_output_input_ratio: 100.0
 
 collator:
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   unit_type: 'spm'
-  spm_model_prefix: 'data/bpe_unigram_5000'
+  spm_model_prefix: 'data/lang_char/bpe_unigram_5000'
   mean_std_filepath: ""
   augmentation_config: conf/preprocess.yaml
   batch_size: 32

examples/librispeech/asr1/local/data.sh

@@ -2,11 +2,12 @@
 
 stage=-1
 stop_stage=100
+dict_dir=data/lang_char
 
 # bpemode (unigram or bpe)
 nbpe=5000
 bpemode=unigram
-bpeprefix="data/bpe_${bpemode}_${nbpe}"
+bpeprefix="${dict_dir}/bpe_${bpemode}_${nbpe}"
 
 stride_ms=10
 window_ms=25
@@ -17,6 +18,7 @@ source ${MAIN_ROOT}/utils/parse_options.sh
 
 
 mkdir -p data
+mkdir -p ${dict_dir}
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 
@@ -79,7 +81,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     --spm_vocab_size=${nbpe} \
     --spm_mode ${bpemode} \
     --spm_model_prefix ${bpeprefix} \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths="data/manifest.train.raw"
 
     if [ $? -ne 0 ]; then
@@ -96,7 +98,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         --cmvn_path "data/mean_std.json" \
         --unit_type "spm" \
         --spm_model_prefix ${bpeprefix} \
-        --vocab_path="data/vocab.txt" \
+        --vocab_path="${dict_dir}/vocab.txt" \
         --manifest_path="data/manifest.${sub}.raw" \
         --output_path="data/manifest.${sub}"
 

examples/ted_en_zh/st0/conf/transformer.yaml

@@ -11,9 +11,9 @@ data:
   max_output_input_ratio: 20.0
 
 collator:
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   unit_type: 'spm'
-  spm_model_prefix: data/bpe_unigram_8000
+  spm_model_prefix: data/lang_char/bpe_unigram_8000
   mean_std_filepath: ""
   # augmentation_config: conf/augmentation.json
   batch_size: 10

examples/ted_en_zh/st0/conf/transformer_joint_noam.yaml

@@ -11,9 +11,9 @@ data:
   max_output_input_ratio: 20.0
 
 collator:
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   unit_type: 'spm'
-  spm_model_prefix: data/bpe_unigram_8000
+  spm_model_prefix: data/lang_char/bpe_unigram_8000
   mean_std_filepath: ""
   # augmentation_config: conf/augmentation.json
   batch_size: 10

examples/ted_en_zh/st0/local/data.sh

@@ -4,19 +4,22 @@ set -e
 
 stage=-1
 stop_stage=100
+dict_dir=data/lang_char
 
 # bpemode (unigram or bpe)
 nbpe=8000
 bpemode=unigram
-bpeprefix="data/bpe_${bpemode}_${nbpe}"
+bpeprefix="${dict_dir}/bpe_${bpemode}_${nbpe}"
 data_dir=./TED-En-Zh
 
 
-source ${MAIN_ROOT}/utils/parse_options.sh
+. ${MAIN_ROOT}/utils/parse_options.sh || exit -1;
+
 
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 mkdir -p data
+mkdir -p ${dict_dir}
 
 
 if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
@@ -73,11 +76,10 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     --spm_vocab_size=${nbpe} \
     --spm_mode ${bpemode} \
     --spm_model_prefix ${bpeprefix} \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --text_keys 'text' 'text1' \
     --manifest_paths="data/manifest.train.raw"
 
-
     if [ $? -ne 0 ]; then
         echo "Build vocabulary failed. Terminated."
         exit 1
@@ -92,7 +94,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         --cmvn_path "data/mean_std.json" \
         --unit_type "spm" \
         --spm_model_prefix ${bpeprefix} \
-        --vocab_path="data/vocab.txt" \
+        --vocab_path="${dict_dir}/vocab.txt" \
         --manifest_path="data/manifest.${set}.raw" \
         --output_path="data/manifest.${set}"
 

examples/ted_en_zh/st1/conf/transformer.yaml

@@ -11,9 +11,9 @@ data:
   max_output_input_ratio: 20.0
 
 collator:
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   unit_type: 'spm'
-  spm_model_prefix: data/bpe_unigram_8000
+  spm_model_prefix: data/lang_char/bpe_unigram_8000
   mean_std_filepath: ""
   # augmentation_config: conf/augmentation.json
   batch_size: 10

examples/ted_en_zh/st1/conf/transformer_mtl_noam.yaml

@@ -11,7 +11,7 @@ data:
   max_output_input_ratio: 20.0
 
 collator:
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   unit_type: 'spm'
   spm_model_prefix: data/train_sp.en-zh-nlpr.zh-nlpr_bpe8000_tc
   mean_std_filepath: ""

examples/ted_en_zh/st1/local/data.sh

@@ -4,11 +4,12 @@ set -e
 
 stage=-1
 stop_stage=100
+dict_dir=data/lang_char
 
 # bpemode (unigram or bpe)
 nbpe=8000
 bpemode=unigram
-bpeprefix="data/bpe_${bpemode}_${nbpe}"
+bpeprefix="${dict_dir}/bpe_${bpemode}_${nbpe}"
 data_dir=./TED_EnZh
 
 
@@ -17,6 +18,7 @@ source ${MAIN_ROOT}/utils/parse_options.sh
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 mkdir -p data
+mkdir -p ${dict_dir}
 
 
 if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
@@ -73,7 +75,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     --spm_vocab_size=${nbpe} \
     --spm_mode ${bpemode} \
     --spm_model_prefix ${bpeprefix} \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --text_keys 'text' 'text1' \
     --manifest_paths="data/manifest.train.raw"
 
@@ -93,7 +95,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         --cmvn_path "data/mean_std.json" \
         --unit_type "spm" \
         --spm_model_prefix ${bpeprefix} \
-        --vocab_path="data/vocab.txt" \
+        --vocab_path="${dict_dir}/vocab.txt" \
         --manifest_path="data/manifest.${set}.raw" \
         --output_path="data/manifest.${set}"
 

examples/timit/asr1/conf/transformer.yaml

@@ -11,7 +11,7 @@ data:
   max_output_input_ratio: 1000.0
 
 collator:
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   unit_type: "word"
   mean_std_filepath: ""
   augmentation_config: conf/preprocess.yaml

examples/timit/asr1/local/data.sh

@@ -3,15 +3,19 @@
 stage=-1
 stop_stage=100
 
+dict_dir=data/lang_char
+
 unit_type=word
 TIMIT_path=
 
-source ${MAIN_ROOT}/utils/parse_options.sh
+. ${MAIN_ROOT}/utils/parse_options.sh || exit -1;
 
 mkdir -p data
+mkdir -p ${dict_dir}
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 
+
 if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
     # download data, generate manifests
     python3 ${TARGET_DIR}/timit/timit_kaldi_standard_split.py \
@@ -52,7 +56,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     python3 ${MAIN_ROOT}/utils/build_vocab.py \
     --unit_type ${unit_type} \
     --count_threshold=0 \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths="data/manifest.train.raw"
 
     if [ $? -ne 0 ]; then
@@ -68,7 +72,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
         python3 ${MAIN_ROOT}/utils/format_data.py \
         --cmvn_path "data/mean_std.json" \
         --unit_type ${unit_type} \
-        --vocab_path="data/vocab.txt" \
+        --vocab_path="${dict_dir}/vocab.txt" \
         --manifest_path="data/manifest.${set}.raw" \
         --output_path="data/manifest.${set}"
 

examples/tiny/asr0/conf/deepspeech2.yaml

@@ -14,7 +14,7 @@ data:
 collator:
   mean_std_filepath: data/mean_std.json
   unit_type: char
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   augmentation_config: conf/augmentation.json
   random_seed: 0
   spm_model_prefix: 

examples/tiny/asr0/conf/deepspeech2_online.yaml

@@ -14,7 +14,7 @@ data:
 collator:
   mean_std_filepath: data/mean_std.json
   unit_type: char
-  vocab_filepath: data/vocab.txt
+  vocab_filepath: data/lang_char/vocab.txt
   augmentation_config: conf/augmentation.json
   random_seed: 0
   spm_model_prefix: 

examples/tiny/asr0/local/data.sh

@@ -4,10 +4,12 @@ stage=-1
 stop_stage=100
 
 unit_type=char
+dict_dir=data/lang_char
 
-source ${MAIN_ROOT}/utils/parse_options.sh
+. ${MAIN_ROOT}/utils/parse_options.sh || exit -1;
 
 mkdir -p data
+mkdir -p ${dict_dir}
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 
@@ -51,7 +53,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     python3 ${MAIN_ROOT}/utils/build_vocab.py \
     --unit_type ${unit_type} \
     --count_threshold=0 \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths="data/manifest.tiny.raw"
     
     if [ $? -ne 0 ]; then
@@ -65,7 +67,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     python3 ${MAIN_ROOT}/utils/format_data.py \
     --cmvn_path "data/mean_std.json" \
     --unit_type ${unit_type} \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_path="data/manifest.tiny.raw" \
     --output_path="data/manifest.tiny"
     

examples/tiny/asr1/conf/chunk_confermer.yaml

@@ -12,7 +12,7 @@ data:
   
 collator:
   mean_std_filepath: ""
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'spm'
   spm_model_prefix: 'data/bpe_unigram_200'
   augmentation_config: conf/preprocess.yaml

examples/tiny/asr1/conf/chunk_transformer.yaml

@@ -12,7 +12,7 @@ data:
   
 collator:
   mean_std_filepath: ""
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'spm'
   spm_model_prefix: 'data/bpe_unigram_200'
   augmentation_config: conf/preprocess.yaml

examples/tiny/asr1/conf/conformer.yaml

@@ -12,7 +12,7 @@ data:
   
 collator:
   mean_std_filepath: ""
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'spm'
   spm_model_prefix: 'data/bpe_unigram_200'
   augmentation_config: conf/preprocess.yaml

examples/tiny/asr1/conf/transformer.yaml

@@ -12,7 +12,7 @@ data:
   
 collator:
   mean_std_filepath: data/mean_std.json
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'spm'
   spm_model_prefix: 'data/bpe_unigram_200'
   augmentation_config: conf/preprocess.yaml

examples/tiny/asr1/local/data.sh

@@ -3,14 +3,17 @@
 stage=-1
 stop_stage=100
 
+dict_dir=data/lang_char
+
 # bpemode (unigram or bpe)
 nbpe=200
 bpemode=unigram
-bpeprefix="data/bpe_${bpemode}_${nbpe}"
+bpeprefix="${dict_dir}/bpe_${bpemode}_${nbpe}"
 
-source ${MAIN_ROOT}/utils/parse_options.sh
+. ${MAIN_ROOT}/utils/parse_options.sh || exit -1;
 
 mkdir -p data
+mkdir -p ${dict_dir}
 TARGET_DIR=${MAIN_ROOT}/examples/dataset
 mkdir -p ${TARGET_DIR}
 
@@ -57,7 +60,7 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
     --spm_vocab_size=${nbpe} \
     --spm_mode ${bpemode} \
     --spm_model_prefix ${bpeprefix} \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_paths="data/manifest.tiny.raw"
     
     if [ $? -ne 0 ]; then
@@ -72,7 +75,7 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     --cmvn_path "data/mean_std.json" \
     --unit_type "spm" \
     --spm_model_prefix ${bpeprefix} \
-    --vocab_path="data/vocab.txt" \
+    --vocab_path="${dict_dir}/vocab.txt" \
     --manifest_path="data/manifest.tiny.raw" \
     --output_path="data/manifest.tiny"
     

examples/wenetspeech/asr1/conf/conformer.yaml

@@ -51,7 +51,7 @@ data:
   max_output_input_ratio: 10.0
 
 collator:
-  vocab_filepath: data/vocab.txt 
+  vocab_filepath: data/lang_char/vocab.txt 
   unit_type: 'char'
   spm_model_prefix: ''
   augmentation_config: conf/preprocess.yaml