Fix preparing char based lang for wenetspeech
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@ -28,6 +28,7 @@ num_splits=1000
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# - speech
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# - speech
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dl_dir=$PWD/download
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dl_dir=$PWD/download
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lang_char_dir=data/lang_char
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. shared/parse_options.sh || exit 1
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. shared/parse_options.sh || exit 1
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@ -186,24 +187,27 @@ fi
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if [ $stage -le 15 ] && [ $stop_stage -ge 15 ]; then
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if [ $stage -le 15 ] && [ $stop_stage -ge 15 ]; then
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log "Stage 15: Prepare char based lang"
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log "Stage 15: Prepare char based lang"
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lang_char_dir=data/lang_char
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mkdir -p $lang_char_dir
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mkdir -p $lang_char_dir
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# Prepare text.
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if ! which jq; then
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# Note: in Linux, you can install jq with the following command:
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echo "This script is intended to be used with jq but you have not installed jq
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# 1. wget -O jq https://github.com/stedolan/jq/releases/download/jq-1.6/jq-linux64
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Note: in Linux, you can install jq with the following command:
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# 2. chmod +x ./jq
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1. wget -O jq https://github.com/stedolan/jq/releases/download/jq-1.6/jq-linux64
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# 3. cp jq /usr/bin
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2. chmod +x ./jq
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if [ ! -f $lang_char_dir/text ]; then
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3. cp jq /usr/bin" && exit 1
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gunzip -c data/manifests/supervisions_L.jsonl.gz \
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fi
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| jq 'text' | sed 's/"//g' \
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if [ ! -f $lang_char_dir/text ] || [ ! -s $lang_char_dir/text ]; then
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log "Prepare text."
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gunzip -c data/manifests/wenetspeech_supervisions_L.jsonl.gz \
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| jq '.text' | sed 's/"//g' \
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| ./local/text2token.py -t "char" > $lang_char_dir/text
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| ./local/text2token.py -t "char" > $lang_char_dir/text
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fi
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fi
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# The implementation of chinese word segmentation for text,
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# The implementation of chinese word segmentation for text,
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# and it will take about 15 minutes.
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# and it will take about 15 minutes.
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if [ ! -f $lang_char_dir/text_words_segmentation ]; then
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if [ ! -f $lang_char_dir/text_words_segmentation ]; then
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python ./local/text2segments.py \
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python3 ./local/text2segments.py \
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--num-process $nj \
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--input-file $lang_char_dir/text \
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--input-file $lang_char_dir/text \
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--output-file $lang_char_dir/text_words_segmentation
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--output-file $lang_char_dir/text_words_segmentation
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fi
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fi
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@ -212,7 +216,7 @@ if [ $stage -le 15 ] && [ $stop_stage -ge 15 ]; then
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| sort -u | sed '/^$/d' | uniq > $lang_char_dir/words_no_ids.txt
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| sort -u | sed '/^$/d' | uniq > $lang_char_dir/words_no_ids.txt
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if [ ! -f $lang_char_dir/words.txt ]; then
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if [ ! -f $lang_char_dir/words.txt ]; then
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python ./local/prepare_words.py \
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python3 ./local/prepare_words.py \
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--input-file $lang_char_dir/words_no_ids.txt \
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--input-file $lang_char_dir/words_no_ids.txt \
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--output-file $lang_char_dir/words.txt
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--output-file $lang_char_dir/words.txt
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fi
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fi
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@ -221,7 +225,7 @@ fi
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if [ $stage -le 16 ] && [ $stop_stage -ge 16 ]; then
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if [ $stage -le 16 ] && [ $stop_stage -ge 16 ]; then
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log "Stage 16: Prepare char based L_disambig.pt"
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log "Stage 16: Prepare char based L_disambig.pt"
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if [ ! -f data/lang_char/L_disambig.pt ]; then
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if [ ! -f data/lang_char/L_disambig.pt ]; then
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python ./local/prepare_char.py \
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python3 ./local/prepare_char.py \
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--lang-dir data/lang_char
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--lang-dir data/lang_char
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fi
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fi
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fi
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fi
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@ -232,9 +236,8 @@ if [ $stage -le 17 ] && [ $stop_stage -ge 17 ]; then
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# It will take about 20 minutes.
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# It will take about 20 minutes.
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# We assume you have install kaldilm, if not, please install
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# We assume you have install kaldilm, if not, please install
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# it using: pip install kaldilm
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# it using: pip install kaldilm
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lang_char_dir=data/lang_char
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if [ ! -f $lang_char_dir/3-gram.unpruned.arpa ]; then
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if [ ! -f $lang_char_dir/3-gram.unpruned.arpa ]; then
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python ./shared/make_kn_lm.py \
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python3 ./shared/make_kn_lm.py \
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-ngram-order 3 \
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-ngram-order 3 \
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-text $lang_char_dir/text_words_segmentation \
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-text $lang_char_dir/text_words_segmentation \
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-lm $lang_char_dir/3-gram.unpruned.arpa
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-lm $lang_char_dir/3-gram.unpruned.arpa
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@ -253,6 +256,5 @@ fi
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if [ $stage -le 18 ] && [ $stop_stage -ge 18 ]; then
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if [ $stage -le 18 ] && [ $stop_stage -ge 18 ]; then
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log "Stage 18: Compile LG"
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log "Stage 18: Compile LG"
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lang_char_dir=data/lang_char
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python ./local/compile_lg.py --lang-dir $lang_char_dir
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python ./local/compile_lg.py --lang-dir $lang_char_dir
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fi
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fi
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