ThreadedConfidenceMeasure.sh
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#-----------------------------------------------------------------------------------------
# Author : Benjamin Lecouteux & Emmanuel FERREIRA (contact emmanuel.ferreira0194@gmail.com)
# Brief: Determine les mesures de confiance d'une transcription (res de speeral)
#-----------------------------------------------------------------------------------------
ROOT=$OTMEDIA_HOME/PACKAGE_MESURES_V1.0
PACKAGE_CONF_MEASURE=$OTMEDIA_HOME/data/cfg/package_measure.cfg
#------------------
# Parser les options
#-------------------
while getopts ":c:s:h" OPTION
do
case $OPTION in
h) #Display help
echo -e "$0 :"
echo -e "\tAuthor : Benjamin Lecouteux & Emmanuel FERREIRA (contact: emmanuel.ferreira0194@gmail.com)"
echo -e "\tVersion : 2.0"
echo -e "\tBrief : Determine confidence measure of a transcription"
echo -e "\tUsage : $0 [OPTIONS] <(i) REP_IN>"
echo -e "\tOptions:"
echo -e "\t\tc) specify the path of the configuration file (default $PACKAGE_CONF_MEASURE)"
echo -e "\t\ts) specify PORT@HOST of a SRILM server"
exit 1
;;
c) #Change the configuration file
PACKAGE_CONF_MEASURE=$OPTARG
;;
s) #use an SRILM server (avoid loading arpa model in memory)
SERVER=$OPTARG
;;
:)
echo "BAD USAGE : OPTION $OPTARG need a value"
exit 1
;;
\?)
echo "BAD USAGE : unknow option '$OPTARG'"
exit 1
;;
esac
done
#-------------------------------------------
# Shift options pour recuperation arguments
#-------------------------------------------
shift $((OPTIND-1))
if [ -z "$1" ]
then
echo "BAD USAGE: $0 [OPTIONS] <(i) repertoire (ex:20041006_0800_0900_CULTURE)>"
exit 1
fi
. $PACKAGE_CONF_MEASURE
#------------------------------------
# INIT - Creation du workspace
#------------------------------------
NAME=`basename $1`
CONF_DIR=$1/conf
REF=$CONF_DIR/ref
POS=$CONF_DIR/pos
MLCLASS=$CONF_DIR/mlclass
GVALIGN=$CONF_DIR/gvalign
HTK_POST=$CONF_DIR/htk_post
HTK_LM=$CONF_DIR/htk_lm
WLAT=$CONF_DIR/wlat
LIKELIHOOD=$CONF_DIR/likelihood
GVCTM=$CONF_DIR/gvctm
SEGCTM=$CONF_DIR/segctm
SUPER_CTM=$CONF_DIR/super_ctm
SCORED_CTM=$CONF_DIR/scored_ctm
mkdir -p $CONF_DIR
mkdir -p $REF
mkdir -p $POS
mkdir -p $MLCLASS
mkdir -p $GVALIGN
mkdir -p $HTK_POST
#mkdir -p $HTK_LM ==> generer auto par SRILM si besoin
mkdir -p $WLAT
mkdir -p $LIKELIHOOD
mkdir -p $GVCTM
mkdir -p $SEGCTM
mkdir -p $SUPER_CTM
mkdir -p $SCORED_CTM
if [ -z $BOOST_BIN ];then
BOOST_BIN=$ROOT/bin/icsiboost-64bit-static-r160
fi
#-----------------------------------------------------------------
# STEP 1 - Extension des treillis + ajout posteriors (format htk)
#-----------------------------------------------------------------
if [ $EXTEND == 1 ]
then
echo "EXTEND step..."
rm -f $HTK_LM/* $HTK_POST/*
#
# --> Ajout des scores linguistiques dans le HTK
#
ls $1/$FICHIER_RES/*.treil > $CONF_DIR/Liste_treil_${NAME}.lst
LM_ACCESS="-lm $ML"
if [ ! -z $SERVER ]; then
LM_ACCESS="-use-server $SERVER -cache-served-ngrams"
fi
rm -r $HTK_LM
#echo "$SRILM_BIN/lattice-tool -read-htk -in-lattice-list $CONF_DIR/Liste_treil_${NAME}.lst $LM_ACCESS -order $ORDER -htk-logbase 10 -htk-lmscale $FUDGE -htk-wdpenalty $PENALITE -write-htk -out-lattice-dir $HTK_LM";
$SRILM_BIN/lattice-tool -read-htk -in-lattice-list $CONF_DIR/Liste_treil_${NAME}.lst $LM_ACCESS -order $ORDER -htk-logbase 10 -htk-lmscale $FUDGE -htk-wdpenalty $PENALITE -write-htk -out-lattice-dir $HTK_LM
#
# --> Calcul des posteriors a partir des scores acoustiques et linguistiques present dans le HTK
#
NbProcess=0
for file in `ls $HTK_LM/*.treil`
do
if [ $NbProcess -ge $MaxProcess ]
then
wait
NbProcess=0
fi
base=`basename $file .treil`;
#echo "lattice-tool -read-htk -in-lattice $file -compute-posteriors -write-htk -out-lattice $HTK_POST/${base}.htk"
$SRILM_BIN/lattice-tool -read-htk -in-lattice $file -compute-posteriors -write-htk -out-lattice $HTK_POST/${base}.htk &
NbProcess=$(( $NbProcess + 1))
done
wait
fi
#---------------------------------------------------------------------------------------------------------------
# STEP 2 - alignement res et wlat pour creer res avec scores + infos (utilise un fastnc modifie)
# Exemple :
# ok amendement 0.814885 ( time=36 nodes=3 min=0.0016862 max=0.814885 mean=0.333896 var=0.363849 svar=0.603199 )
#----------------------------------------------------------------------------------------------------------------
if [ $FASTNC == 1 ]
then
echo "FASTNC step..."
rm -f $POS/* $WLAT/*
NbProcess=0
for file in `ls $HTK_LM/*.treil`
do
if [ $NbProcess -ge $MaxProcess ]
then
wait
NbProcess=0
fi
base=`basename $file .treil`;
#echo "$ROOT/bin/fastnc_v1.4 $HTK_POST/${base}.htk $WLAT/${base}.wlat $1/$FICHIER_RES/${base}.res rien -dtw2 > $POS/$base.pos2&"
$ROOT/bin/fastnc_v1.4 $HTK_POST/${base}.htk $WLAT/${base}.wlat $1/$FICHIER_RES/${base}.res rien -dtw2 > $POS/$base.pos2 &
NbProcess=$(( $NbProcess + 1))
done
wait
fi
#------------------------------------------------------------------------------------------------------------
# STEP 3 - recuperation de la probabilite pour chaque mot + info relatives au modele de langue (backoff, ...)
#------------------------------------------------------------------------------------------------------------
if [ $PPL == 1 ]
then
echo "PPL step..."
rm -f $REF/* $CONF_DIR/${NAME}_ALLREF.* $MLCLASS/*
#
# --> Creation des references a partir des .res (uniquement si .treil present)
#
for file in `ls $1/$FICHIER_RES/*.res`
do
base=`basename $file .res`;
if [ -f $1/$FICHIER_RES/$base.treil ];then
cat $file | cut -f5 -d' ' | tr "\n" " " > $REF/${base}.ref
fi
done
#
# --> creation d'un fichier contenant l'ensemble des transcriptions du show
#
compteur=0
for file in `du -sh $REF/*.ref | grep -v "^0" | cut -f2`
do
base=`basename $file .ref`;
cat $file >> $CONF_DIR/${NAME}_ALLREF.txt
echo "" >> $CONF_DIR/${NAME}_ALLREF.txt
ListeFichiers[$compteur]=$base.mlclass
compteur=$(( $compteur + 1 ))
done
#
# --> recuperation de la probabilite pour chaque mot provenant des resultats de l'ASR + informations linguistiques (backoff used, ngram,...)
#
$SRILM_BIN/ngram -lm $ML -order $ORDER -ppl $CONF_DIR/${NAME}_ALLREF.txt -debug 2 > $CONF_DIR/${NAME}_ALLREF.mlclass
#
# --> creation d'un fichier par fichier .ref
#
compteur=0
cat $CONF_DIR/${NAME}_ALLREF.mlclass | while read line
do
echo $line | grep "^$" > /dev/null
if [ $? == 0 ];then
compteur=$(( $compteur + 1 ))
else
echo "$line" | grep "p(" > /dev/null
if [ $? == 0 ];then
echo "$line" >> $MLCLASS/${ListeFichiers[${compteur}]};
fi
fi
done
fi
#----------------------------------------------------------
# STEP 4 - recuperation du score acoustique de chaque mot
#----------------------------------------------------------
if [ $ACOUST == 1 ]
then
echo "ACOUST step..."
rm -f $GVALIGN/* $GVCTM/* $SEGCTM/* $LIKELIHOOD/*
for file in `ls $1/$FICHIER_RES/*.res`
do
base=`basename $file .res`
if [ -f $1/$FICHIER_RES/$base.treil ];then
#echo "$ROOT/script/MakeListForGVAlign.pl $file $GVALIGN";
$ROOT/script/MakeListForGVAlign.pl $file $GVALIGN
fi
done
NbProcess=0
for file in `ls $GVALIGN/*.gvalign`
do
base=`basename $file .gvalign`;
type=`echo $base | cut -f2 -d: | cut -f2- -d\# | sed -e "s/[0-9]\+//"`
case "$type" in
"M#S")
HMM=$mod_ms
;;
"F#S")
HMM=$mod_fs
;;
"M#T")
HMM=$mod_mt
;;
"F#T")
HMM=$mod_ft
;;
esac
if [ $NbProcess -ge $MaxProcess ]
then
wait
NbProcess=0
fi
#echo "$ROOT/bin/gvalign.old $HMM $PHON $file -e $1/${REP_PLP}/ -f .plp -r $GVALIGN -g .gv -C FAST -W $GVCTM -O CTM -s $SEGCTM > $LIKELIHOOD/${base}.likelihood | sed -e 's/Decoding/\\nDecoding/g' > $LIKELIHOOD/${base}.likelihood";
$ROOT/bin/gvalign.old $HMM $PHON $file -e $1/${REP_PLP}/ -f .plp -r $GVALIGN -g .gv -C FAST -W $GVCTM -O CTM -s $SEGCTM | sed -e 's/Decoding/\nDecoding/g' > $LIKELIHOOD/${base}.likelihood &
NbProcess=$(( $NbProcess + 1))
done
wait
fi
#--------------------------------------------------------------------------------------------------------------------------------
# STEP 5 - Merge de tous les scores caclules => res (ctm) avec scores/params utiliser dans la classif
# Format :
# mot NbNode MinNode MaxNode MeanNode VarNode SVarNode Posterior AcousticLogLikelihood AcousticLogLikelihood/Frame ...
# AcousticConfidenceLikelihood AcousticConstraintLikeLihood AcousticNoConstraint Likelihood ClasseRepliLinguistique ...
# RepliLinguistique LogLinguistique LogUnigramme NbMotsFenetre NbNulNode NbTrame
#---------------------------------------------------------------------------------------------------------------------------------
if [ $EXTRACT == 1 ]
then
echo "EXTRACT step..."
rm -f $SUPER_CTM/*
for file in `ls $1/$FICHIER_RES/*.res`
do
base=`basename $file .res`;
like=`echo "$base" | sed -e 's/\..*//'`;
if [ -f $1/$FICHIER_RES/$base.treil ]; then
#echo "$ROOT/script/ExtractData.pl $pathML $nameML $POS/${base}.pos2 $file $LIKELIHOOD/${like}.likelihood $MLCLASS/${base}.mlclass $TYPE_ML > $SUPER_CTM/${base}.ctm";
$ROOT/script/ExtractData.pl $pathML $nameML $POS/${base}.pos2 $file $LIKELIHOOD/${like}.likelihood $MLCLASS/${base}.mlclass $TYPE_ML > $SUPER_CTM/${base}.ctm
fi
done
fi
#----------------------------------------------------------------
# STEP 6 - Calcul effectif du score de confiance pour chaque mot
#----------------------------------------------------------------
if [ $BOOST == 1 ]
then
echo "BOOST step..."
rm -f $SCORED_CTM/* $CONF_DIR/${NAME}.sctm $CONF_DIR/${NAME}.boost* $CONF_DIR/${NAME}.resboost* $CONF_DIR/${NAME}.corres*
# utilise pour le test sans etiquette
$ROOT/script/DissociateErroneousFromDecoded.pl $SUPER_CTM 2 equilibre > $CONF_DIR/${NAME}.sctm
$ROOT/script/ConvertSuperCTMtoDataSVM.pl $CONF_DIR/${NAME}.sctm boost 2 0 0 > $CONF_DIR/${NAME}.boost
$ROOT/script/ConvertSuperCTMtoDataSVM.pl $CONF_DIR/${NAME}.sctm boost 2 0 1 > $CONF_DIR/${NAME}.boost_refs
$BOOST_BIN -S $ROOT/TRAIN -C --posteriors < $CONF_DIR/${NAME}.boost > $CONF_DIR/${NAME}.resboost
cat $CONF_DIR/${NAME}.resboost | cut -f4 -d" " > $CONF_DIR/${NAME}.resboost2
cat $CONF_DIR/${NAME}.boost_refs | sed -e 's/.*ref=//' > $CONF_DIR/${NAME}.corres
paste $CONF_DIR/${NAME}.corres $CONF_DIR/${NAME}.resboost2 | sed -e 's/\.ctm/\.res/' > $CONF_DIR/${NAME}.corres2
$ROOT/script/AssociateScoreToCtm.pl $CONF_DIR/${NAME}.corres2 $1/$FICHIER_RES/ $SCORED_CTM/
fi
echo "END"