NAME

       slmbuild - generate language model from idngram file

SYNOPSIS

       slmbuild [option]... idngram_file...

DESCRIPTION

       slmbuild generates a back-off smoothing language model from a given idngram file.
       Generally, the idngram_file is created by ids2ngram.

OPTIONS All the following options are mandatory.

       -n,--NMax N
           1 for unigram, 2 for bigram, 3 for trigram. Any number not in the range of 1..3 is not
           valid.

       -o, --out output-file
           Specify the output xfilei name.

       -l, --log
           using -log(pr), use pr directly by default.

       -w, --wordcount N
           Lexican size, number of different words.

       -b, --brk id...
           Set the ids which should be treated as breaker.

       -e, --e id...
           Set the ids which should not be put into LM.

       -c, --cut c...
           k-grams whose freq <= c[k] are dropped.

       -d, --discount method, param...
           The k-th -d parm specifies the discount method

           For k-gram, possibble values for method/param are:

                 B<GT>,I<R>,I<dis>  : B<GT> discount for r E<lt>= I<R>, r is the freq of a ngram.
                             Linear discount for those r E<gt> I<R>, i.e. r'=r*dis
                             0 E<lt>E<lt> dis E<lt> 1.0, for example 0.999
                 B<ABS>,[I<dis>] : Absolute discount r'=r-I<dis>. And I<dis> is optional
                             0 E<lt>E<lt> I<dis> E<lt> cut[k]+1.0, normally I<dis> E<lt> 1.0.
                 LIN,[I<dis>] : Linear discount r'=r*dis. And dis is optional
                             0 E<lt> dis E<lt> 1.0

NOTE

       -n must be given before -c -b. And -c must give right number of cut-off, also -ds must
       appear exactly N times specifying the discounts for 1-gram, 2-gram..., respectively.

       BREAKER-IDs could be SentenceTokens or ParagraphTokens. Conceptually, these ids have no
       meaning when they appeared in the middle of n-gram.

       EXCLUDE-IDs could be ambiguious-ids. Conceptually, n-grams which contain those ids are
       meaningless.

       We can not erase ngrams according to BREAKER-IDS and EXCLUDE-IDs directly from IDNGRAM
       file, because some low-level information is still useful in it.

EXAMPLE

       Following example read 'all.id3gram' and write trigram model 'all.slm'.

       At 1-gram level, use Good-Turing discount with cut-off 0, i<R>=8, dis=0.9995. At 2-gram
       level, use Absolute discount with cut-off 3, dis auto-calc. At 3-gram level, use Absolute
       discount with cut-off 2, dis auto-calc. Word id 10,11,12 are breakers (sentence/para/paper
       breaker, etc). Exclude-ID is 9. Lexicon contains 200000 words. The result languagme model
       uses -log(pr).

       slmbuild -l -n 3 -o all.slm -w 200000 -c 0,3,2 -d GT,8,0.9995 -d ABS -d ABS -b 10,11,12 -e
       9 all.id3gram

AUTHOR

       Originally written by Phill.Zhang <phill.zhang@sun.com>.  Currently maintained by Kov.Chai
       <tchaikov@gmail.com>.

SEE ALSO

       ids2ngram(1), slmprune(1).