makelm

It is the Speech recognition software. It is platform independent. To execute the source code,

#
# Generates the language model for a 'weather' vocabulary
#
# uses:
#       weather.txt - transcript of weather forecasts
#       weather.vocab - hand prepared vocabulary list
#
# generates:
#       weather.lm - arpa format of the language model
#       weather.DMP - CMU binary format of the language model
#       weather.transcript - transcript
#
#       
# requires:
#       CMU language model toolkit:
#               http://www.speech.cs.cmu.edu/SLM_info.html
#       lm3g2dmp - utility to generate DMP format models:
#           http://cmusphinx.sourceforge.net/webpage/html/download.php#utilities#
# unix commands:
#       gawk uniq mv rmdir rm
#
# All commands should be in your path
#

bn=weather.txt

# We want a closed vocabulary language model so we use
# extractVocab to extract just the sentences that entirely
# match our vocabulary

gawk -f extractVocab.awk weather.vocab  weather.txt  > $bn.tmp.closed


#
# We generate the 'test' file that can be used by the live decoder
# as the prompt for the user. We eliminate adjacent duplicate entries

gawk -f genTranscript.awk < $bn.tmp.closed > weather.transcript

#
# Generate the word frequencies
#

text2wfreq < $bn.tmp.closed > $bn.tmp.wfreq

#
# Generate the vocabulary (this should be a subset weather.vocab)
#

wfreq2vocab  < $bn.tmp.wfreq > $bn.tmp.vocab

#
# Generate the idngram

text2idngram -vocab $bn.tmp.vocab < $bn.tmp.closed  > $bn.tmp.idngram


#
# generates the language model

idngram2lm -vocab_type 0 -idngram $bn.tmp.idngram -vocab $bn.tmp.vocab -arpa $bn.arpa


#
# generate the DMP version of the language model
#

mkdir dmp
lm3g2dmp $bn.arpa dmp
mv dmp/$bn.arpa.DMP weather.DMP
mv $bn.arpa weather.lm

#
# cleanup
#

rmdir dmp
rm *.tmp.*