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Scripts/utils/rnnlm_compute_scores.sh
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#!/bin/bash # Compute scores from RNNLM. This script takes a directory # $dir (e.g. dir=local/rnnlm/rnnlm.voc30.hl30 ), # where it expects the files: # rnnlm wordlist.rnn unk.probs, # and also an input file location where it can get the sentences to score, and # an output file location to put the scores (negated logprobs) for each # sentence. This script uses the Kaldi-style "archive" format, so the input and # output files will have a first field that corresponds to some kind of # utterance-id or, in practice, utterance-id-1, utterance-id-2, etc., for the # N-best list. # # Here, "wordlist.rnn" is the set of words, like a vocabulary, # that the RNN was trained on (note, it won't include <s> or </s>), # plus <RNN_UNK> which is a kind of class where we put low-frequency # words; unk.probs gives the probs for words given this class, and it # has, on each line, "word prob". . ./path.sh || exit 1; rnnlm=$KALDI_ROOT/tools/rnnlm-0.3e/rnnlm [ ! -f $rnnlm ] && echo No such program $rnnlm && exit 1; if [ $# != 4 ]; then echo "Usage: rnnlm_compute_scores.sh <rnn-dir> <temp-dir> <input-text> <output-scores>" exit 1; fi dir=$1 tempdir=$2 text_in=$3 scores_out=$4 for x in rnnlm wordlist.rnn unk.probs; do if [ ! -f $dir/$x ]; then echo "rnnlm_compute_scores.sh: expected file $dir/$x to exist." exit 1; fi done mkdir -p $tempdir cat $text_in | awk '{for (x=2;x<=NF;x++) {printf("%s ", $x)} printf(" ");}' >$tempdir/text cat $text_in | awk '{print $1}' > $tempdir/ids # e.g. utterance ids. cat $tempdir/text | awk -v voc=$dir/wordlist.rnn -v unk=$dir/unk.probs \ -v logprobs=$tempdir/loglikes.oov \ 'BEGIN{ while((getline<voc)>0) { invoc[$1]=1; } while ((getline<unk)>0){ unkprob[$1]=$2;} } { logprob=0; for (x=1;x<=NF;x++) { w=$x; if (invoc[w]) { printf("%s ",w); } else { printf("<RNN_UNK> "); if (unkprob[w] != 0) { logprob += log(unkprob[w]); } else { print "Warning: unknown word ", w >"/dev/stderr"; logprob += log(1.0e-07); }}} printf(" "); print logprob > logprobs } ' > $tempdir/text.nounk # OK, now we compute the scores on the text with OOVs replaced # with <RNN_UNK> $rnnlm -independent -rnnlm $dir/rnnlm -test $tempdir/text.nounk -nbest -debug 0 | \ awk '{print $1*log(10);}' > $tempdir/loglikes.rnn [ `cat $tempdir/loglikes.rnn | wc -l` -ne `cat $tempdir/loglikes.oov | wc -l` ] && \ echo "rnnlm rescoring failed" && exit 1; paste $tempdir/loglikes.rnn $tempdir/loglikes.oov | awk '{print -($1+$2);}' >$tempdir/scores # scores out, with utterance-ids. paste $tempdir/ids $tempdir/scores > $scores_out |