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71 lines
2.7 KiB
71 lines
2.7 KiB
2 years ago
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#!/bin/bash
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# To be run from one directory above this script.
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. ./path.sh
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nj=40
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text=data/local/lm/text
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lexicon=data/local/dict/lexicon.txt
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for f in "$text" "$lexicon"; do
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[ ! -f $x ] && echo "$0: No such file $f" && exit 1;
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done
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# Check SRILM tools
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if ! which ngram-count > /dev/null; then
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echo "srilm tools are not found, please download it and install it from: "
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echo "http://www.speech.sri.com/projects/srilm/download.html"
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echo "Then add the tools to your PATH"
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exit 1
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fi
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# This script takes no arguments. It assumes you have already run
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# aishell_data_prep.sh.
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# It takes as input the files
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# data/local/lm/text
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# data/local/dict/lexicon.txt
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dir=data/local/lm
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mkdir -p $dir
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cleantext=$dir/text.no_oov
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# oov to <SPOKEN_NOISE>
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# lexicon line: word char0 ... charn
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# text line: utt word0 ... wordn -> line: <SPOKEN_NOISE> word0 ... wordn
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text_dir=$(dirname $text)
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split_name=$(basename $text)
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./local/split_data.sh $text_dir $text $split_name $nj
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utils/run.pl JOB=1:$nj $text_dir/split${nj}/JOB/${split_name}.no_oov.log \
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cat ${text_dir}/split${nj}/JOB/${split_name} \| awk -v lex=$lexicon 'BEGIN{while((getline<lex) >0){ seen[$1]=1; } }
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{for(n=1; n<=NF;n++) { if (seen[$n]) { printf("%s ", $n); } else {printf("<SPOKEN_NOISE> ");} } printf("\n");}' \
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\> ${text_dir}/split${nj}/JOB/${split_name}.no_oov || exit 1;
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cat ${text_dir}/split${nj}/*/${split_name}.no_oov > $cleantext
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# compute word counts, sort in descending order
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# line: count word
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cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | sort --parallel=`nproc` | uniq -c | \
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sort --parallel=`nproc` -nr > $dir/word.counts || exit 1;
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# Get counts from acoustic training transcripts, and add one-count
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# for each word in the lexicon (but not silence, we don't want it
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# in the LM-- we'll add it optionally later).
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cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | \
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cat - <(grep -w -v '!SIL' $lexicon | awk '{print $1}') | \
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sort --parallel=`nproc` | uniq -c | sort --parallel=`nproc` -nr > $dir/unigram.counts || exit 1;
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# word with <s> </s>
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cat $dir/unigram.counts | awk '{print $2}' | cat - <(echo "<s>"; echo "</s>" ) > $dir/wordlist
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# hold out to compute ppl
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heldout_sent=10000 # Don't change this if you want result to be comparable with kaldi_lm results
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mkdir -p $dir
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cat $cleantext | awk '{for(n=2;n<=NF;n++){ printf $n; if(n<NF) printf " "; else print ""; }}' | \
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head -$heldout_sent > $dir/heldout
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cat $cleantext | awk '{for(n=2;n<=NF;n++){ printf $n; if(n<NF) printf " "; else print ""; }}' | \
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tail -n +$heldout_sent > $dir/train
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ngram-count -text $dir/train -order 3 -limit-vocab -vocab $dir/wordlist -unk \
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-map-unk "<UNK>" -kndiscount -interpolate -lm $dir/lm.arpa
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ngram -lm $dir/lm.arpa -ppl $dir/heldout
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