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55 lines
1.8 KiB
55 lines
1.8 KiB
#!/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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src=ds2_graph_with_slot
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text=$src/train_text
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lexicon=$src/local/dict/lexicon.txt
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dir=$src/local/lm
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mkdir -p $dir
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for f in "$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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pushd $MAIN_ROOT/tools
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make srilm.done
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popd
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fi
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# This script takes no arguments. It assumes you have already run
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# It takes as input the files
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# data/local/lm/text
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# data/local/dict/lexicon.txt
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cleantext=$dir/text.no_oov
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cat $text | awk -v lex=$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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> $cleantext || exit 1;
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cat $cleantext | awk '{for(n=2;n<=NF;n++) print $n; }' | sort | uniq -c | \
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sort -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 | uniq -c | sort -nr > $dir/unigram.counts || exit 1;
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# filter the words which are not in the text
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cat $dir/unigram.counts | awk '$1>1{print $0}' | awk '{print $2}' | cat - <(echo "<s>"; echo "</s>" ) > $dir/wordlist
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# 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 ""; }}' > $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>" -gt3max 0 -gt2max 0 -gt1max 0 -lm $dir/lm.arpa
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#ngram-count -text $dir/train -order 3 -limit-vocab -vocab $dir/wordlist -unk \
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# -map-unk "<UNK>" -lm $dir/lm2.arpa |