#!/bin/bash # Copyright Johns Hopkins University (Author: Daniel Povey) 2012. Apache 2.0. # This script produces CTM files from a training directory that has alignments # present. # begin configuration section. cmd=run.pl stage=0 use_segments=true # if we have a segments file, use it to convert # the segments to be relative to the original files. #end configuration section. [ -f ./path.sh ] && . ./path.sh . parse_options.sh || exit 1; if [ $# -ne 3 ]; then echo "Usage: local/get_train_ctm.sh [options] " echo " Options:" echo " --cmd (run.pl|queue.pl...) # specify how to run the sub-processes." echo " --stage (0|1|2) # start scoring script from part-way through." echo " --use-segments (true|false) # use segments and reco2file_and_channel files " echo " # to produce a ctm relative to the original audio" echo " # files, with channel information (typically needed" echo " # for NIST scoring)." echo "e.g.:" echo "local/get_train_ctm.sh data/train data/lang exp/tri3a_ali" echo "Produces ctm in: exp/tri3a_ali/ctm" exit 1; fi data=$1 lang=$2 # Note: may be graph directory not lang directory, but has the necessary stuff copied. dir=$3 model=$dir/final.mdl # assume model one level up from decoding dir. for f in $lang/words.txt $lang/phones/word_boundary.int \ $model $dir/ali.1.gz $lang/oov.int; do [ ! -f $f ] && echo "$0: expecting file $f to exist" && exit 1; done oov=`cat $lang/oov.int` || exit 1; mkdir -p $dir/scoring/log if [ $stage -le 0 ]; then if [ -f $data/segments ]; then f=$data/reco2file_and_channel [ ! -f $f ] && echo "$0: expecting file $f to exist" && exit 1; filter_cmd="utils/convert_ctm.pl $data/segments $data/reco2file_and_channel" else filter_cmd=cat fi $cmd $dir/log/get_ctm.log \ linear-to-nbest "ark:gunzip -c $dir/ali.*.gz|" \ "ark:utils/sym2int.pl --map-oov $oov -f 2- $lang/words.txt < $data/text |" \ '' '' ark:- \| \ lattice-align-words $lang/phones/word_boundary.int $model ark:- ark:- \| \ nbest-to-ctm ark:- - \| \ utils/int2sym.pl -f 5 $lang/words.txt \| \ $filter_cmd '>' $dir/ctm || exit 1; fi